Dataset statistics
| Number of variables | 26 |
|---|---|
| Number of observations | 1296 |
| Missing cells | 0 |
| Missing cells (%) | 0.0% |
| Duplicate rows | 838 |
| Duplicate rows (%) | 64.7% |
| Total size in memory | 263.4 KiB |
| Average record size in memory | 208.1 B |
Variable types
| CAT | 13 |
|---|---|
| NUM | 7 |
| BOOL | 6 |
| Dataset has 838 (64.7%) duplicate rows | Duplicates |
Job Title has a high cardinality: 201 distinct values | High cardinality |
Salary Estimate has a high cardinality: 392 distinct values | High cardinality |
Job Description has a high cardinality: 457 distinct values | High cardinality |
Company Name has a high cardinality: 400 distinct values | High cardinality |
Location has a high cardinality: 198 distinct values | High cardinality |
Industry has a high cardinality: 65 distinct values | High cardinality |
max_salary is highly correlated with min_salary and 1 other fields | High correlation |
min_salary is highly correlated with max_salary and 1 other fields | High correlation |
avg_salary is highly correlated with min_salary and 1 other fields | High correlation |
Sector is highly correlated with Industry | High correlation |
Industry is highly correlated with Sector | High correlation |
Reproduction
| Analysis started | 2020-12-09 20:32:20.427495 |
|---|---|
| Analysis finished | 2020-12-09 20:32:33.277997 |
| Duration | 12.85 seconds |
| Software version | pandas-profiling v2.9.0 |
| Download configuration | config.yaml |
| Distinct | 201 |
|---|---|
| Distinct (%) | 15.5% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| Data Scientist | |
|---|---|
| Machine Learning Engineer | 48 |
| Data Science Instructor | 39 |
| Analytical Chemist/Scientist for Biologics Group | 39 |
| Full Stack Data Scientist | 38 |
| Other values (196) |
| Value | Count | Frequency (%) | |
| Data Scientist | 790 | 61.0% | |
| Machine Learning Engineer | 48 | 3.7% | |
| Data Science Instructor | 39 | 3.0% | |
| Analytical Chemist/Scientist for Biologics Group | 39 | 3.0% | |
| Full Stack Data Scientist | 38 | 2.9% | |
| Data Scientist- Logistics Delivery Team | 38 | 2.9% | |
| Data Engineer | 14 | 1.1% | |
| Senior Data Scientist | 7 | 0.5% | |
| Senior Data Engineer | 5 | 0.4% | |
| Big Data Engineer | 5 | 0.4% | |
| Other values (191) | 273 | 21.1% |
Unique
| Unique | 138 ? |
|---|---|
| Unique (%) | 10.6% |
Length
| Max length | 76 |
|---|---|
| Median length | 14 |
| Mean length | 20.59182099 |
| Min length | 12 |
simplified_title
Categorical
| Distinct | 10 |
|---|---|
| Distinct (%) | 0.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| Data Scientist | |
|---|---|
| Other Scientist | 62 |
| Machine Learning Engineer | 56 |
| Data Engineer | 50 |
| Data Analyst | 46 |
| Other values (5) | 84 |
| Value | Count | Frequency (%) | |
| Data Scientist | 998 | 77.0% | |
| Other Scientist | 62 | 4.8% | |
| Machine Learning Engineer | 56 | 4.3% | |
| Data Engineer | 50 | 3.9% | |
| Data Analyst | 46 | 3.5% | |
| Instructor | 39 | 3.0% | |
| Other | 20 | 1.5% | |
| Other Analyst | 15 | 1.2% | |
| Research Scientist | 9 | 0.7% | |
| Research Analyst | 1 | 0.1% |
Unique
| Unique | 1 ? |
|---|---|
| Unique (%) | 0.1% |
Length
| Max length | 25 |
|---|---|
| Median length | 14 |
| Mean length | 14.1720679 |
| Min length | 5 |
seniority
Categorical
| Distinct | 4 |
|---|---|
| Distinct (%) | 0.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| na | |
|---|---|
| Senior | 95 |
| Mid-level | 7 |
| Junior | 5 |
| Value | Count | Frequency (%) | |
| na | 1189 | 91.7% | |
| Senior | 95 | 7.3% | |
| Mid-level | 7 | 0.5% | |
| Junior | 5 | 0.4% |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Length
| Max length | 9 |
|---|---|
| Median length | 2 |
| Mean length | 2.346450617 |
| Min length | 2 |
| Distinct | 392 |
|---|---|
| Distinct (%) | 30.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| $107K-$170K (Glassdoor est.) | 41 |
|---|---|
| $65K-$109K (Glassdoor est.) | 40 |
| $100K-$160K (Glassdoor est.) | 40 |
| $54K-$97K (Glassdoor est.) | 40 |
| $94K-$155K (Glassdoor est.) | 40 |
| Other values (387) |
| Value | Count | Frequency (%) | |
| $107K-$170K (Glassdoor est.) | 41 | 3.2% | |
| $65K-$109K (Glassdoor est.) | 40 | 3.1% | |
| $100K-$160K (Glassdoor est.) | 40 | 3.1% | |
| $54K-$97K (Glassdoor est.) | 40 | 3.1% | |
| $94K-$155K (Glassdoor est.) | 40 | 3.1% | |
| $36K-$55K (Glassdoor est.) | 39 | 3.0% | |
| $121K-$196K (Glassdoor est.) | 39 | 3.0% | |
| $81K-$133K (Glassdoor est.) | 39 | 3.0% | |
| $72K-$124K (Glassdoor est.) | 39 | 3.0% | |
| $63K-$107K (Glassdoor est.) | 39 | 3.0% | |
| Other values (382) | 900 | 69.4% |
Unique
| Unique | 233 ? |
|---|---|
| Unique (%) | 18.0% |
Length
| Max length | 42 |
|---|---|
| Median length | 27 |
| Mean length | 26.99459877 |
| Min length | 25 |
| Distinct | 109 |
|---|---|
| Distinct (%) | 8.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 74.37962963 |
|---|---|
| Minimum | 12 |
| Maximum | 155 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 10.1 KiB |
Quantile statistics
| Minimum | 12 |
|---|---|
| 5-th percentile | 36.75 |
| Q1 | 60 |
| median | 70 |
| Q3 | 90 |
| 95-th percentile | 118.25 |
| Maximum | 155 |
| Range | 143 |
| Interquartile range (IQR) | 30 |
Descriptive statistics
| Standard deviation | 22.92275466 |
|---|---|
| Coefficient of variation (CV) | 0.308185921 |
| Kurtosis | -0.2630969483 |
| Mean | 74.37962963 |
| Median Absolute Deviation (MAD) | 15 |
| Skewness | 0.4177498383 |
| Sum | 96396 |
| Variance | 525.4526813 |
| Monotocity | Not monotonic |
| Value | Count | Frequency (%) | |
| 60 | 88 | 6.8% | |
| 62 | 82 | 6.3% | |
| 65 | 54 | 4.2% | |
| 88 | 53 | 4.1% | |
| 72 | 50 | 3.9% | |
| 50 | 47 | 3.6% | |
| 94 | 45 | 3.5% | |
| 81 | 45 | 3.5% | |
| 107 | 45 | 3.5% | |
| 36 | 44 | 3.4% | |
| Other values (99) | 743 | 57.3% |
| Value | Count | Frequency (%) | |
| 12 | 4 | 0.3% | |
| 18 | 1 | 0.1% | |
| 21 | 1 | 0.1% | |
| 24 | 1 | 0.1% | |
| 27 | 1 | 0.1% |
| Value | Count | Frequency (%) | |
| 155 | 1 | 0.1% | |
| 149 | 1 | 0.1% | |
| 142 | 1 | 0.1% | |
| 136 | 1 | 0.1% | |
| 135 | 2 | 0.2% |
| Distinct | 134 |
|---|---|
| Distinct (%) | 10.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 122.4621914 |
|---|---|
| Minimum | 49 |
| Maximum | 247 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 10.1 KiB |
Quantile statistics
| Minimum | 49 |
|---|---|
| 5-th percentile | 73 |
| Q1 | 102 |
| median | 118 |
| Q3 | 145 |
| 95-th percentile | 187 |
| Maximum | 247 |
| Range | 198 |
| Interquartile range (IQR) | 43 |
Descriptive statistics
| Standard deviation | 33.93732751 |
|---|---|
| Coefficient of variation (CV) | 0.2771249407 |
| Kurtosis | -0.04702318889 |
| Mean | 122.4621914 |
| Median Absolute Deviation (MAD) | 21 |
| Skewness | 0.4567026784 |
| Sum | 158711 |
| Variance | 1151.742199 |
| Monotocity | Not monotonic |
| Value | Count | Frequency (%) | |
| 109 | 82 | 6.3% | |
| 107 | 81 | 6.2% | |
| 124 | 52 | 4.0% | |
| 102 | 50 | 3.9% | |
| 119 | 49 | 3.8% | |
| 133 | 48 | 3.7% | |
| 97 | 45 | 3.5% | |
| 104 | 44 | 3.4% | |
| 92 | 43 | 3.3% | |
| 170 | 42 | 3.2% | |
| Other values (124) | 760 | 58.6% |
| Value | Count | Frequency (%) | |
| 49 | 1 | 0.1% | |
| 51 | 1 | 0.1% | |
| 53 | 1 | 0.1% | |
| 55 | 41 | 3.2% | |
| 56 | 3 | 0.2% |
| Value | Count | Frequency (%) | |
| 247 | 1 | 0.1% | |
| 234 | 1 | 0.1% | |
| 227 | 1 | 0.1% | |
| 225 | 1 | 0.1% | |
| 223 | 1 | 0.1% |
| Distinct | 192 |
|---|---|
| Distinct (%) | 14.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 98.42091049 |
|---|---|
| Minimum | 35 |
| Maximum | 201 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 10.1 KiB |
Quantile statistics
| Minimum | 35 |
|---|---|
| 5-th percentile | 55.375 |
| Q1 | 80 |
| median | 94.5 |
| Q3 | 117 |
| 95-th percentile | 150.5 |
| Maximum | 201 |
| Range | 166 |
| Interquartile range (IQR) | 37 |
Descriptive statistics
| Standard deviation | 28.03782805 |
|---|---|
| Coefficient of variation (CV) | 0.2848767392 |
| Kurtosis | -0.1924233617 |
| Mean | 98.42091049 |
| Median Absolute Deviation (MAD) | 17.75 |
| Skewness | 0.4583134187 |
| Sum | 127553.5 |
| Variance | 786.1198018 |
| Monotocity | Not monotonic |
| Value | Count | Frequency (%) | |
| 85 | 77 | 5.9% | |
| 107 | 46 | 3.5% | |
| 75.5 | 45 | 3.5% | |
| 74.5 | 43 | 3.3% | |
| 130 | 43 | 3.3% | |
| 98 | 43 | 3.3% | |
| 138.5 | 42 | 3.2% | |
| 124.5 | 40 | 3.1% | |
| 83 | 40 | 3.1% | |
| 87 | 40 | 3.1% | |
| Other values (182) | 837 | 64.6% |
| Value | Count | Frequency (%) | |
| 35 | 1 | 0.1% | |
| 37.5 | 1 | 0.1% | |
| 41 | 1 | 0.1% | |
| 43 | 1 | 0.1% | |
| 43.5 | 1 | 0.1% |
| Value | Count | Frequency (%) | |
| 201 | 1 | 0.1% | |
| 191.5 | 1 | 0.1% | |
| 182.5 | 1 | 0.1% | |
| 180.5 | 1 | 0.1% | |
| 179.5 | 1 | 0.1% |
hourly
Boolean
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| 0 | |
|---|---|
| 1 | 3 |
| Value | Count | Frequency (%) | |
| 0 | 1293 | 99.8% | |
| 1 | 3 | 0.2% |
employer_provided_salary
Boolean
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| 0 | |
|---|---|
| 1 | 5 |
| Value | Count | Frequency (%) | |
| 0 | 1291 | 99.6% | |
| 1 | 5 | 0.4% |
| Distinct | 457 |
|---|---|
| Distinct (%) | 35.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| Job Title: Data Scientist Location: US, California, San Jose Role Overview: Looking to have an impact? Come be a part of the change as we move into a new era at McAfee. Mission driven, both at the company and functional level, we share a passion for customers at the core. Critical, highly visible role reporting into Director of Analytics, Sr Experimentation Analyst/ Data Analyst will and will own all aspects of the product experimentation program with the goal of driving data based decisions Company Overview From device to cloud, McAfee provides market-leading cybersecurity solutions for both business and consumers. We help businesses orchestrate cyber environments that are truly integrated, where protection, detection, and correction of security threats happen simultaneously. For consumers, McAfee secures your devices against viruses, malware, and other threats, both at home and away. We want to continue to shape the future of cybersecurity by working together to build best in class products and solutions. About the role: Partner with product, marketing and technology organizations to develop and deliver data basedbusiness insights and solutions Use your expert knowledge of data in our data lake and reporting databases to evaluate business opportunities, size projects, conduct analysisand prototype data solutions Own end to end processof defining and publishing KPIs and metrics including getting agreement from stakeholders, validation, documentation, standardization across organization and driving automation Help Increase the adoption of data solutions by educating users anddeveloping user friendly documentation Conduct exploratory data analysis and hypothesis driven deep dives into consumer behavior and subscription data to uncover opportunities through unique insights to improve consumer experience and monetization Conduct analysis onA/B testing data to help find winners, drive new ideas for testing and promote the use of A/B testing as a tool for decision making. Combine your business and technical knowledge to drive value from data utilizing a variety of methodologies like descriptive and predictive analytics, statistics ,experimentation, and business intelligence Act as a subject matter expert for business and engineering teams on data in our data lake and various operational databases About you: 7+ years of experience in Business or Data Analytics 3+ experience running, analyzing and managing A/B tests Experience in developing reports and dashboards utilizing industry standard BI tools ( Microstrategy or Tableau preferred) Expertise in presenting data and analysis at all levels in the organization Expert level SQL knowledge required Knowledge of python data analysis frameworks like pandas preferred Knowledge of statistical package like R preferred Experience with online consumer data required Demonstrated strong collaboration skills and ability to work cross functionally Demonstrated ability to effectively communicate with both technical and non-technical audience Master's degree in Mathematics, Statistics, Engineering or Business Company Benefits and Perks: We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees. Pension and Retirement Plans Medical, Dental and Vision Coverage Paid Time Off Paid Parental Leave Support for Community Involvement We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status. Job Type: Experienced Hire Primary Location: US, California, San Jose Additional Locations: | 40 |
|---|---|
| Machine Learning Engineer 10835 Phoenix, AZ 7/13/2020 11:11:00 AM IT Contractor - W2 Job Description Job Description – Python/ML – Senior Engineer/ Architect Site Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space. What you will be doing: Conceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach Research latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability Develop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering Qualifications: A BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience 5 + years of experience in Python with emphasis on machine learning Hands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn Experience in designing mission critical highly available enterprise applications Strong knowledge of Linux internals and experience managing Linux systems in high traffic environments Strong knowledge of machine learning, mathematical modeling, R, and statistics Strong interpersonal communication skills and the ability to work well in a diverse team-focused environment 5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred Knowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred Job Requirements Job Description – Python/ML – Senior Engineer/ Architect Site Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space. What you will be doing: Conceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach Research latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability Develop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering Qualifications: A BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience 5 + years of experience in Python with emphasis on machine learning Hands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn Experience in designing mission critical highly available enterprise applications Strong knowledge of Linux internals and experience managing Linux systems in high traffic environments Strong knowledge of machine learning, mathematical modeling, R, and statistics Strong interpersonal communication skills and the ability to work well in a diverse team-focused environment 5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred Knowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred | 40 |
| Position Purpose: The primary purpose of this position is to serve as the data scientist with a split portfolio between the Atlantic City office and the Austin chemistry group. Essential Duties and Responsibilities: Performs data analytics, specifically data clean-up, data processing, predictive modeling, chemometric statistical modeling and analysis, multivariate data analysis, machine learning, and/or data mining, as related to scientific data. Applies technical skills to plan and execute assigned project work including development of computational models, programming of detection algorithms, and machine learning. Maintains operational capabilities of computation assets as needed by project requirements. Leads meetings with company clients by preparing and presenting meeting materials in meetings. Appropriately annotates project developed computer code through comments and user manuals. Presents technical results through the drafting of technical reports. Presents experimental results and recommended actions at internal project meetings. Supports business development efforts as needed by drafting technical sections of proposals, providing proposal review, assessing levels of effort required to complete proposed work, and brainstorming technical solutions to client problems. Other duties as assigned. Required Knowledge, Skills & Abilities (KSA's): Required KSA's Ability to plan sequence of experiments to answer complicated technical questions Ability to lead group of co-workers in execution of a task Software programming proficiency with Java, C, R, Python, and/or MATLAB Working knowledge of statistics as it applies to scientific data Ability to communicate technical information to non-technical audiences Team player with a positive attitude Preferred KSA's Department of Homeland Security Suitability Department of Defense Secret Clearance Working knowledge of software development practices including Agile development and Git version control Sufficient business knowledge to support proposal efforts Education/Experience: Incumbent professional should have a Ph.D. or master's degree in a physical science (preferably chemistry), statistics, or data science and significant experience in computer programming, computational modeling, or software development. Certificates and Licenses: No specific certificates or licenses are required for this position. Clearance: The ability to obtain a Secret clearance and Department of Homeland Security suitability is required for this position. Supervisory Responsibilities: The incumbent professional may oversee junior level staff members performing tasks. Working Conditions/ Equipment: The incumbent professional is expected to work and/or be available during regular business hours. He/she should also generally be available via e-mail or phone during non-business hours as needed to address critical issues or emergencies. He/she may be required to travel on behalf of the company up to 25%. The above job description is not intended to be an all-inclusive list of duties and standards of the position. Incumbents will follow any other instructions and perform any other related duties, as assigned by their supervisor. | 39 |
| About the Opportunity Are you looking for a fast paced position in a rapidly growing company? We are seeking an Analytical Chemist/Scientist for our Biologics Group in Ann Arbor, Michigan. We are searching for talented and motivated individuals that would enjoy working in a team oriented, entrepreneurial company. Job Description and Responsibilities Learn techniques spanning across the entire spectrum of analytical chemistry from wet chemistry to HPLC, NMR, Mass Spectrometry, FTIR, GC and GC-MS Perform testing using a variety of technologies including HPLC, LC-MS, GC, GC/MS, Microscopy, FTIR and UV Execute projects in support of client needs including product deformulation and product development, failure analysis and problem solving, impurity identification, extractable and leachable studies, and structural characterization Follow all safety requirements including wearing appropriate personal protective equipment Generate supporting laboratory documentation Ensure compliance with government rules and regulations (FDA, cGMP, DEA, ICH, OSHA, etc.) Implement new equipment and processes independently, capable of conducting appropriate qualification and validation activities Execute projects with minimal supervision Have the ability to analyze data from the qualitative to the rigorously statistical and defend conclusions based on data Have the ability to demonstrate strong problem-solving and analytical abilities Requirements Experience with analytical method development Experience with protein mass spectrometry, proteomics (LC-MS/MS or LC-QTOF) Experience with mammalian cell culture Experience working with proteins and nucleic acids Experience with HPLC or FPLC Effective scientific writer (experience with report writing) Effective oral presenter (experience with scientific presentations) Effective time management Must be a flexible, adaptable, self-driven team player with a positive attitude Preferred Hands-on experience with AAV or lentivirus Hands-on experience with viral transduction assays Experience with capillary electrophoresis Experience with GC-MS Experience with method validation Experience with MALDI or TOF Experience with QC method development/validation Bachelor's degree (preferred) 3-7 years’ experience Why Work for Us? Avomeen is a full-service laboratory with unique analytical, product testing and formulation development expertise. Each member of the Avomeen team plays a critical and visible role in delivering high-quality scientific solutions, providing them with an opportunity to directly impact Avomeen’s success and advance their career. We make every effort to reward outstanding performance and provide interesting and scientifically challenging work. In order to ensure the success, development, and growth of our employees, we are committed to offering a variety of training opportunities. Become Part of our Community We recognize that our single greatest resource is our people, and our team members choose Avomeen not only to join our scientific knowledge-based community, but also to become part of a collaborative team committed to exemplary science and service to our clients. Successful Avomeen employees have a positive, client-centric outlook, and embody principles of integrity and leadership, as well as creativity, flexibility, and perseverance. | 39 |
| Join our team dedicated to developing and executing innovative solutions in support of customer mission success. Job Description: Novetta is seeking a skilled Data Science Instructor to support a fast paced, innovative project supporting our client in the field of data science and AI/Machine Learning. Basic Qualifications: SME skill level 15+ years of experience in data science or a related field Ability to become familiar with current client priorities, programs and issues in order to adapt training programs to reflect changes in client mission, structure, regulations, or processes. Excellent oral, written, and interpersonal communication skills Outstanding facilitation skills to manage group processes and elicit student participation Analytic and problem-solving skills Demonstrated ability to apply structured analysis methods to various types of data to establish trends, determine variability, and diagnose the effect on training curricula. Ability to work independently and as part of a team Security Clearance: An active TS/SCI w/Poly clearance Novetta, from complexity to clarity. Novetta delivers highly scalable advanced analytics and secure technology solutions to address challenges of national and global significance. Focused on mission success, Novetta pioneers disruptive technologies in machine learning, data analytics, full-spectrum cyber, cloud engineering, open source analytics, and multi-INT fusion for Defense, Intelligence Community, and Federal Law Enforcement customers. Novetta is headquartered in McLean, VA with over 1,000 employees across the U.S. Our culture is shaped by a commitment to our core values: Integrity • We hold ourselves accountable to the highest standards of integrity and ethics. Customer Success • We strive daily to exceed expectations and achieve customer mission success. Employee Focus • We invest in our employees' professional development and training, respecting individuality, and fostering a culture of diversity and inclusion. Innovation • We know that discovering new and innovative ways to solve problems is critical to our success and makes us a great company. Excellence in Execution • We take pride in flawless execution as we build a company that is best in class. Earn a REFERRAL BONUS for the qualified people you know. For more details or to submit a referral, visit bit.ly/NovettaReferrals. Novetta is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. | 39 |
| Other values (452) |
| Value | Count | Frequency (%) | |
| Job Title: Data Scientist Location: US, California, San Jose Role Overview: Looking to have an impact? Come be a part of the change as we move into a new era at McAfee. Mission driven, both at the company and functional level, we share a passion for customers at the core. Critical, highly visible role reporting into Director of Analytics, Sr Experimentation Analyst/ Data Analyst will and will own all aspects of the product experimentation program with the goal of driving data based decisions Company Overview From device to cloud, McAfee provides market-leading cybersecurity solutions for both business and consumers. We help businesses orchestrate cyber environments that are truly integrated, where protection, detection, and correction of security threats happen simultaneously. For consumers, McAfee secures your devices against viruses, malware, and other threats, both at home and away. We want to continue to shape the future of cybersecurity by working together to build best in class products and solutions. About the role: Partner with product, marketing and technology organizations to develop and deliver data basedbusiness insights and solutions Use your expert knowledge of data in our data lake and reporting databases to evaluate business opportunities, size projects, conduct analysisand prototype data solutions Own end to end processof defining and publishing KPIs and metrics including getting agreement from stakeholders, validation, documentation, standardization across organization and driving automation Help Increase the adoption of data solutions by educating users anddeveloping user friendly documentation Conduct exploratory data analysis and hypothesis driven deep dives into consumer behavior and subscription data to uncover opportunities through unique insights to improve consumer experience and monetization Conduct analysis onA/B testing data to help find winners, drive new ideas for testing and promote the use of A/B testing as a tool for decision making. Combine your business and technical knowledge to drive value from data utilizing a variety of methodologies like descriptive and predictive analytics, statistics ,experimentation, and business intelligence Act as a subject matter expert for business and engineering teams on data in our data lake and various operational databases About you: 7+ years of experience in Business or Data Analytics 3+ experience running, analyzing and managing A/B tests Experience in developing reports and dashboards utilizing industry standard BI tools ( Microstrategy or Tableau preferred) Expertise in presenting data and analysis at all levels in the organization Expert level SQL knowledge required Knowledge of python data analysis frameworks like pandas preferred Knowledge of statistical package like R preferred Experience with online consumer data required Demonstrated strong collaboration skills and ability to work cross functionally Demonstrated ability to effectively communicate with both technical and non-technical audience Master's degree in Mathematics, Statistics, Engineering or Business Company Benefits and Perks: We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees. Pension and Retirement Plans Medical, Dental and Vision Coverage Paid Time Off Paid Parental Leave Support for Community Involvement We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status. Job Type: Experienced Hire Primary Location: US, California, San Jose Additional Locations: | 40 | 3.1% | |
| Machine Learning Engineer 10835 Phoenix, AZ 7/13/2020 11:11:00 AM IT Contractor - W2 Job Description Job Description – Python/ML – Senior Engineer/ Architect Site Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space. What you will be doing: Conceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach Research latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability Develop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering Qualifications: A BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience 5 + years of experience in Python with emphasis on machine learning Hands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn Experience in designing mission critical highly available enterprise applications Strong knowledge of Linux internals and experience managing Linux systems in high traffic environments Strong knowledge of machine learning, mathematical modeling, R, and statistics Strong interpersonal communication skills and the ability to work well in a diverse team-focused environment 5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred Knowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred Job Requirements Job Description – Python/ML – Senior Engineer/ Architect Site Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space. What you will be doing: Conceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach Research latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability Develop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering Qualifications: A BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience 5 + years of experience in Python with emphasis on machine learning Hands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn Experience in designing mission critical highly available enterprise applications Strong knowledge of Linux internals and experience managing Linux systems in high traffic environments Strong knowledge of machine learning, mathematical modeling, R, and statistics Strong interpersonal communication skills and the ability to work well in a diverse team-focused environment 5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred Knowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred | 40 | 3.1% | |
| Position Purpose: The primary purpose of this position is to serve as the data scientist with a split portfolio between the Atlantic City office and the Austin chemistry group. Essential Duties and Responsibilities: Performs data analytics, specifically data clean-up, data processing, predictive modeling, chemometric statistical modeling and analysis, multivariate data analysis, machine learning, and/or data mining, as related to scientific data. Applies technical skills to plan and execute assigned project work including development of computational models, programming of detection algorithms, and machine learning. Maintains operational capabilities of computation assets as needed by project requirements. Leads meetings with company clients by preparing and presenting meeting materials in meetings. Appropriately annotates project developed computer code through comments and user manuals. Presents technical results through the drafting of technical reports. Presents experimental results and recommended actions at internal project meetings. Supports business development efforts as needed by drafting technical sections of proposals, providing proposal review, assessing levels of effort required to complete proposed work, and brainstorming technical solutions to client problems. Other duties as assigned. Required Knowledge, Skills & Abilities (KSA's): Required KSA's Ability to plan sequence of experiments to answer complicated technical questions Ability to lead group of co-workers in execution of a task Software programming proficiency with Java, C, R, Python, and/or MATLAB Working knowledge of statistics as it applies to scientific data Ability to communicate technical information to non-technical audiences Team player with a positive attitude Preferred KSA's Department of Homeland Security Suitability Department of Defense Secret Clearance Working knowledge of software development practices including Agile development and Git version control Sufficient business knowledge to support proposal efforts Education/Experience: Incumbent professional should have a Ph.D. or master's degree in a physical science (preferably chemistry), statistics, or data science and significant experience in computer programming, computational modeling, or software development. Certificates and Licenses: No specific certificates or licenses are required for this position. Clearance: The ability to obtain a Secret clearance and Department of Homeland Security suitability is required for this position. Supervisory Responsibilities: The incumbent professional may oversee junior level staff members performing tasks. Working Conditions/ Equipment: The incumbent professional is expected to work and/or be available during regular business hours. He/she should also generally be available via e-mail or phone during non-business hours as needed to address critical issues or emergencies. He/she may be required to travel on behalf of the company up to 25%. The above job description is not intended to be an all-inclusive list of duties and standards of the position. Incumbents will follow any other instructions and perform any other related duties, as assigned by their supervisor. | 39 | 3.0% | |
| About the Opportunity Are you looking for a fast paced position in a rapidly growing company? We are seeking an Analytical Chemist/Scientist for our Biologics Group in Ann Arbor, Michigan. We are searching for talented and motivated individuals that would enjoy working in a team oriented, entrepreneurial company. Job Description and Responsibilities Learn techniques spanning across the entire spectrum of analytical chemistry from wet chemistry to HPLC, NMR, Mass Spectrometry, FTIR, GC and GC-MS Perform testing using a variety of technologies including HPLC, LC-MS, GC, GC/MS, Microscopy, FTIR and UV Execute projects in support of client needs including product deformulation and product development, failure analysis and problem solving, impurity identification, extractable and leachable studies, and structural characterization Follow all safety requirements including wearing appropriate personal protective equipment Generate supporting laboratory documentation Ensure compliance with government rules and regulations (FDA, cGMP, DEA, ICH, OSHA, etc.) Implement new equipment and processes independently, capable of conducting appropriate qualification and validation activities Execute projects with minimal supervision Have the ability to analyze data from the qualitative to the rigorously statistical and defend conclusions based on data Have the ability to demonstrate strong problem-solving and analytical abilities Requirements Experience with analytical method development Experience with protein mass spectrometry, proteomics (LC-MS/MS or LC-QTOF) Experience with mammalian cell culture Experience working with proteins and nucleic acids Experience with HPLC or FPLC Effective scientific writer (experience with report writing) Effective oral presenter (experience with scientific presentations) Effective time management Must be a flexible, adaptable, self-driven team player with a positive attitude Preferred Hands-on experience with AAV or lentivirus Hands-on experience with viral transduction assays Experience with capillary electrophoresis Experience with GC-MS Experience with method validation Experience with MALDI or TOF Experience with QC method development/validation Bachelor's degree (preferred) 3-7 years’ experience Why Work for Us? Avomeen is a full-service laboratory with unique analytical, product testing and formulation development expertise. Each member of the Avomeen team plays a critical and visible role in delivering high-quality scientific solutions, providing them with an opportunity to directly impact Avomeen’s success and advance their career. We make every effort to reward outstanding performance and provide interesting and scientifically challenging work. In order to ensure the success, development, and growth of our employees, we are committed to offering a variety of training opportunities. Become Part of our Community We recognize that our single greatest resource is our people, and our team members choose Avomeen not only to join our scientific knowledge-based community, but also to become part of a collaborative team committed to exemplary science and service to our clients. Successful Avomeen employees have a positive, client-centric outlook, and embody principles of integrity and leadership, as well as creativity, flexibility, and perseverance. | 39 | 3.0% | |
| Join our team dedicated to developing and executing innovative solutions in support of customer mission success. Job Description: Novetta is seeking a skilled Data Science Instructor to support a fast paced, innovative project supporting our client in the field of data science and AI/Machine Learning. Basic Qualifications: SME skill level 15+ years of experience in data science or a related field Ability to become familiar with current client priorities, programs and issues in order to adapt training programs to reflect changes in client mission, structure, regulations, or processes. Excellent oral, written, and interpersonal communication skills Outstanding facilitation skills to manage group processes and elicit student participation Analytic and problem-solving skills Demonstrated ability to apply structured analysis methods to various types of data to establish trends, determine variability, and diagnose the effect on training curricula. Ability to work independently and as part of a team Security Clearance: An active TS/SCI w/Poly clearance Novetta, from complexity to clarity. Novetta delivers highly scalable advanced analytics and secure technology solutions to address challenges of national and global significance. Focused on mission success, Novetta pioneers disruptive technologies in machine learning, data analytics, full-spectrum cyber, cloud engineering, open source analytics, and multi-INT fusion for Defense, Intelligence Community, and Federal Law Enforcement customers. Novetta is headquartered in McLean, VA with over 1,000 employees across the U.S. Our culture is shaped by a commitment to our core values: Integrity • We hold ourselves accountable to the highest standards of integrity and ethics. Customer Success • We strive daily to exceed expectations and achieve customer mission success. Employee Focus • We invest in our employees' professional development and training, respecting individuality, and fostering a culture of diversity and inclusion. Innovation • We know that discovering new and innovative ways to solve problems is critical to our success and makes us a great company. Excellence in Execution • We take pride in flawless execution as we build a company that is best in class. Earn a REFERRAL BONUS for the qualified people you know. For more details or to submit a referral, visit bit.ly/NovettaReferrals. Novetta is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. | 39 | 3.0% | |
| Job Description Job Description Summary Advance Auto Parts, a leader in the automotive aftermarket, currently has an opening for a Data Scientist. As a Data Scientist at Advance Auto Parts, you will have an opportunity to disrupt a $100B auto parts industry to bring better and faster solutions to customers. You will be responsible for analyzing billions of transactions to find patterns that will help improve our company and build data products to extract valuable business insights as it relates to assortment planning and inventory optimization. You will be part of an elite data science team formed to help the organization live its mission of Advancing a World in Motion. Job Description Essential Duties and Responsibilities include the following. Identify and implement strategies to leverage various large data sources for purposes of improving assortment availability Collect, analyze, and interpret information from multiple data sources identifying actionable insights that create efficiencies and generate revenue. Build predictive models and machine-learning algorithms for second-level analytics and assortment related processes Develop reports and/or presentations leveraging data visualization tools that clearly and concisely communicate analytical findings and recommendations to key stakeholders. Analyze customer sales, transaction, and vehicle related data to identify trends and patterns for use in improving store assortments Familiarity with ANSI SQL Conduct digital channel analysis to understand traffic and revenue drivers, both in-store and on-line. Leverage analytical tools (SQL, Python, R) and data mining techniques to perform advanced data manipulation and extract insights from large databases. Support ad hoc data analysis as requested. Demonstrated desire for continued learning and keeping up with latest techniques in the field of statistics, predictive analytics, operations research or related focuses. Capable of working both independently and on team projects. Other duties may be assigned. Required Qualifications Capable of performing the duties listed above. Proven understanding of latest modeling and forecasting techniques. Skilled with python programming techniques, unit testing, documentation. Familiarity with AWS, Notebooks, Hadoop, EMR and S3 a plus. Familiarity with agile project management a plus. EDUCATION and/or EXPERIENCE Bachelors Degree in Computer Science, Mathematics, Engineering or other relevant disciplines Understanding of relational databases and experience with data mining. Minimum of 2 years of work experience in a field related to data science. Preferred Qualifications Masters Degree or PhD in Data Science or another quantitative field. | 39 | 3.0% | |
| At Jabil, we empower the brands who empower the world – it’s our reason for being and the guiding force that’s driving us to become the most technologically advanced manufacturing solutions provider on the planet. Whether we’re serving one of the world’s biggest and best known brands or the coolest tech startups, our resolve never wavers. We share common desires with these brands: to make the world a better, safer and cleaner place. JOB QUALIFICATIONS KNOWLEDGE REQUIREMENTS ● Advanced Statistics, operations research/ management, mathematics or business analytics with experience, courses, or project work in an analytic methods such as linear, mixed linear, constraint programming, modeling, simulation, time series analysis, pattern recognition, queuing theory, multivariate analysis, and other various predictive analytics techniques ● Strong written and verbal communication skills and the ability to work effectively in teams and under pressure. Multi-lingual capability is a plus. ● Ability to draw conclusions from data and prescribe actionable and measurable activities. ● Highly motivated and creative, thinking “out of the box”. ● Familiarity with non-relational data frameworks (aka NoSQL, eg. Hive). ● Experience with Apache Pig, Spark systems. ● Strong team mentality, interpersonal and communications skills ● Preferred working directly with management and executives Jabil, including its subsidiaries, is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identify, age, disability, genetic information, veteran status, or any other characteristic protected by law. | 38 | 2.9% | |
| The Challenge: Are you excited at the prospect of unlocking the secrets held by a data set? Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances? In an increasingly connected world, massive amounts of structured and unstructured data open up new opportunities. As a data scientist, you can turn these complex data sets into useful information to solve global challenges. Across private and public sectors — from fraud detection, to cancer research, to national intelligence — you know the answers are in the data. We have an opportunity for you to use your analytical skills to improve decision-making in the intelligence community (IC). You’ll work closely with your customer to understand their questions and needs, and then dig into their data-rich environment to find the pieces of their information puzzle. You’ll develop machine learning algorithms, predictive analytics, and Web applications to provide your customer with a deep understanding of their data, what it all means, and how they can use it. Join us as we use data science for good in improving decision-making in the intelligence community. Empower change with us. You Have: -Experience with Python to perform rapid prototyping of data analysis, mining, and data visualization -Experience with creating front-end applications using JavaScript, HTML5, and CSS3, and programming with C++ -Experience in developing applications with UI and UX design -Experience with the application of advanced data science and data analytics, including structured, unstructured, or relational and data mining and machine learning techniques -Experience with server systems administration or configuration tasks in Windows or Linux environments -Ability to exhibit flexibility, initiative, and innovation to succeed in an ambiguous and fast-paced environment to compose client deliverable quality documentation, analysis, and reports -TS/SCI clearance with a polygraph -BA or BS in CS, Data Science, Statistics, Mathematics, or Engineering Nice If You Have: -Experience with data visualization and knowledge object creation using Splunk and Tableau a plus -Experience with Java -Experience with time series and geo-temporal data analysis -Experience with Agile methodologies -Experience with Big Data analytics, including Hadoop, Spark, and TensorFlow, graph analytics, and natural language processing -Possession of excellent oral and written communication and consulting skills -MA or MS degree or PhD degree in CS, Data Science, Statistics, Mathematics, Technology, Science, or Engineering preferred Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with polygraph is required. Build Your Career: At Booz Allen, we know the power of analytics and we’re dedicated to helping you grow as a data analysis professional. When you join Booz Allen, you can expect: access to online and onsite training in data analysis and presentation methodologies, and tools like Hortonworks, Docker, Tableau, and Splunk a chance to change the world with the Data Science Bowl—the world’s premier data science for social good competition participation in partnerships with data science leaders, like our partnership with NVIDIA to deliver Deep Learning Institute (DLI) training to the federal government You’ll have access to a wealth of training resources through our Analytics University, an online learning portal specifically geared towards data science and analytics skills, where you can access more than 5000 functional and technical courses, certifications, and books. Build your technical skills through hands-on training on the latest tools and state-of-the-art tech from our in-house experts. Pursuing certifications? Take advantage of our tuition assistance, on-site boot camps, certification training, academic programs, vendor relationships, and a network of professionals who can give you helpful tips. We’ll help you develop the career you want, as you chart your own course for success. We’re an EOE that empowers our people—no matter their race, color, religion, sex, gender identity, sexual orientation, national origin, disability, veteran status, or other protected characteristic—to fearlessly drive change. #LI-AH1, CMD, NSG1 | 38 | 2.9% | |
| Role Overview: Looking for data scientists that will help us discover and leverage digital retail data to help our clients drive top line sales and add meaningful value to their businesses. Primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated into our various platforms. In addition, applying advanced machine learning techniques where appropriately to improve performance of the Decision Science solutions. Key Accountabilities: Own data science projects through full cycle implementation Perform analysis to predict outcomes based on business questions/problems Processing, cleansing, and verifying the integrity of data used for analysis including normalization, standardization, PCA, correlation, data wrangling, etc. Selecting features, building and optimizing classifiers using machine learning techniques Data mining using state-of-the-art methods including but not limited to K-means, kNN, Neural Networks, Decision Trees, Random Forests, Logistic Regression, Linear/Multiple Regression, etc Doing ad-hoc analysis and presenting results in a clear manner Market Mix Models Quantify what drove sales changes looking at metrics such as Average Selling Price, Out of Stock, Coupons, Discounts, Media attributed clicks, etc. Utilize results to help our clients make better investment choices to drive incremental sales Integrate models into our internal dashboard to visualize and make output of models easily accessible Media Analytics Participate in media innovation groups to test and learn new ways of setting up and running media campaigns on Amazon (AMS, AAP), and other online retailers including but not limited to Instacart, Walmart, Target, Kroger, Shipt, etc. Develop and test models to move from manual and rule-based campaign management to programmatic campaign management Hypothesis Testing Perform hypothesis testing to better understand data sets and comparison of data sets. The following tests might include but are not limited to Normality Testing, T-Test, Chi-Square Test, ANOVA, HOV, etc. Coach team members less experience in the field of ML Skills, Experience, Qualifications Required: We’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field Experience with programmatic media, Google ads, Facebook Advertising, etc. is a plus Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc Experience querying databases and using statistical computer languages: R, Python, SQL, etc. Excellence in at least R or Python is highly desirable Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. Experience with data visualisation tools, such as D3.js, GGplot, Tableau, etc. Excellent written and verbal communication skills for coordinating across teams What we offer: Our benefits package incorporates what we’re passionate about – unlocking your future, overall well-being, and sustainability – whilst giving you control over your benefits. Unlimited Paid Time Off 401K – Saving Incentive plan Medical and Dental Insurance plans Flexible Spending Accounts Vision benefits Great learning and development opportunities Life Assurance and Disability insurance Option to opt into the Ascential Shares Scheme About Flywheel Flywheel Digital is a diverse collection of practitioners who have solved the most challenging problems for numerous Fortune 500 companies on Amazon. We love rolling up our sleeves to figure out the root cause of issues and implement structural fixes to get and keep our client's business on track. Our team of business managers, search managers, analysts, and software developers work together to provide industry-leading support to the best brands on Amazon. Flywheel are headquartered in Baltimore in the United States and have recently set up a European hub in London. In 2018 Flywheel was acquired by Ascential PLC. Want more info? Find out more on what our people say: Ascential YouTube Channel If we inspire you, why not join and inspire us? | 38 | 2.9% | |
| Do you love developing creative solutions to challenging problems? Are you passionate about providing real impact to the countrys toughest national security problems? Are you searching for engaging work with an employer that prioritizes continual innovation? If so, we are looking for someone like you to join our team at APL. The Large-Scale Analytics Group (QAS) develops software systems that incorporate artificial intelligence (AI) and machine learning (ML) algorithms on big data platforms and graph databases as well as visual analytics to find details hidden deep within large and complex data sets. We support multiple agencies within the US Government by applying innovative analytics to uncover activities such as epidemic hotspots, illegal activities, international trade fraud, illicit manufacturing of weapons of mass destruction, and cyber-crime. You will implement and apply computationally tractable solutions and corresponding data architectures to address the needs of our sponsors. We are seeking a confident leader, creative thinker, motivated problem solver, standout colleague, and life-long learner that wants to strengthen the safety and security of our country. You will join a hardworking team in an inclusive environment that cultivates intellectual curiosity, innovation and creativity. As a Data Scientist you will... Primarily design creative AI and ML algorithms as well as analytic pipelines for analyzing large-scale and complex data. Develop data architectures using technologies like Hadoop, Spark, and distributed graphs to support analytic algorithms. Build software applications and perform analytics on complex data. Clearly present results to both JHU/APL and Sponsor leadership. Potentially travel locally to sponsor sites on an occasional basis. You meet our minimum qualifications for this position if you Possess a B.S. in Computer Science, Information Science, Mathematics, Physics, Operations Research, or a related discipline. 1-5 years of experience. Have experience with statistics, machine learning algorithms, or general algorithm development. Have a knowledge of modern large-scale data systems and architectures. Possess solid software development skills. Exhibit excellent social skills, the ability to work independently, excellent written and oral communications skills, and good organizational skills. Are able to obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship. Youll go above and beyond our minimum requirements if you Have a M.S. or Ph.D. in the disciplines listed above, and have working knowledge of state-of-the-art large-scale data approaches and architectures. e.g. experience with quantum algorithms. Are experienced with software engineering processes and techniques. Why Work at APL? The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nations most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates. At APL, we celebrate our differences and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APLs campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at www.jhuapl.edu/careers. | 38 | 2.9% | |
| Other values (447) | 908 | 70.1% |
Unique
| Unique | 312 ? |
|---|---|
| Unique (%) | 24.1% |
Length
| Max length | 14394 |
|---|---|
| Median length | 3682 |
| Mean length | 3977.737654 |
| Min length | 659 |
description_length
Real number (ℝ≥0)
| Distinct | 433 |
|---|---|
| Distinct (%) | 33.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 3977.737654 |
|---|---|
| Minimum | 659 |
| Maximum | 14394 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 10.1 KiB |
Quantile statistics
| Minimum | 659 |
|---|---|
| 5-th percentile | 1714 |
| Q1 | 2702 |
| median | 3682 |
| Q3 | 4847.75 |
| 95-th percentile | 7646 |
| Maximum | 14394 |
| Range | 13735 |
| Interquartile range (IQR) | 2145.75 |
Descriptive statistics
| Standard deviation | 1694.221754 |
|---|---|
| Coefficient of variation (CV) | 0.4259259663 |
| Kurtosis | 1.960446432 |
| Mean | 3977.737654 |
| Median Absolute Deviation (MAD) | 1010 |
| Skewness | 1.096971895 |
| Sum | 5155148 |
| Variance | 2870387.352 |
| Monotocity | Not monotonic |
| Value | Count | Frequency (%) | |
| 3906 | 40 | 3.1% | |
| 3781 | 40 | 3.1% | |
| 4986 | 40 | 3.1% | |
| 3210 | 39 | 3.0% | |
| 6553 | 39 | 3.0% | |
| 2702 | 39 | 3.0% | |
| 3323 | 39 | 3.0% | |
| 2725 | 39 | 3.0% | |
| 2361 | 38 | 2.9% | |
| 4312 | 38 | 2.9% | |
| Other values (423) | 905 | 69.8% |
| Value | Count | Frequency (%) | |
| 659 | 2 | 0.2% | |
| 703 | 1 | 0.1% | |
| 941 | 2 | 0.2% | |
| 960 | 2 | 0.2% | |
| 991 | 1 | 0.1% |
| Value | Count | Frequency (%) | |
| 14394 | 1 | 0.1% | |
| 14232 | 1 | 0.1% | |
| 9741 | 2 | 0.2% | |
| 9538 | 2 | 0.2% | |
| 9466 | 1 | 0.1% |
contains_python
Boolean
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| 1 | |
|---|---|
| 0 |
| Value | Count | Frequency (%) | |
| 1 | 858 | 66.2% | |
| 0 | 438 | 33.8% |
contains_R
Boolean
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| 0 | |
|---|---|
| 1 |
| Value | Count | Frequency (%) | |
| 0 | 1029 | 79.4% | |
| 1 | 267 | 20.6% |
contains_big_data
Boolean
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| 0 | |
|---|---|
| 1 |
| Value | Count | Frequency (%) | |
| 0 | 676 | 52.2% | |
| 1 | 620 | 47.8% |
contains_MS
Boolean
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| 1 | |
|---|---|
| 0 |
| Value | Count | Frequency (%) | |
| 1 | 658 | 50.8% | |
| 0 | 638 | 49.2% |
Rating
Real number (ℝ)
| Distinct | 31 |
|---|---|
| Distinct (%) | 2.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 3.729166667 |
|---|---|
| Minimum | -1 |
| Maximum | 5 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 10.1 KiB |
Quantile statistics
| Minimum | -1 |
|---|---|
| 5-th percentile | 3 |
| Q1 | 3.5 |
| median | 3.7 |
| Q3 | 4 |
| 95-th percentile | 4.6 |
| Maximum | 5 |
| Range | 6 |
| Interquartile range (IQR) | 0.5 |
Descriptive statistics
| Standard deviation | 0.5246050178 |
|---|---|
| Coefficient of variation (CV) | 0.1406762059 |
| Kurtosis | 9.605927166 |
| Mean | 3.729166667 |
| Median Absolute Deviation (MAD) | 0.2 |
| Skewness | -1.036498681 |
| Sum | 4833 |
| Variance | 0.2752104247 |
| Monotocity | Not monotonic |
| Value | Count | Frequency (%) | |
| 3.8 | 165 | 12.7% | |
| 3.5 | 149 | 11.5% | |
| 3.9 | 134 | 10.3% | |
| 3.6 | 132 | 10.2% | |
| 3.1 | 93 | 7.2% | |
| 3.7 | 81 | 6.2% | |
| 3.3 | 74 | 5.7% | |
| 4.5 | 65 | 5.0% | |
| 4.3 | 63 | 4.9% | |
| 4.6 | 57 | 4.4% | |
| Other values (21) | 283 | 21.8% |
| Value | Count | Frequency (%) | |
| -1 | 2 | 0.2% | |
| 2 | 2 | 0.2% | |
| 2.1 | 1 | 0.1% | |
| 2.2 | 1 | 0.1% | |
| 2.4 | 5 | 0.4% |
| Value | Count | Frequency (%) | |
| 5 | 11 | 0.8% | |
| 4.9 | 4 | 0.3% | |
| 4.8 | 6 | 0.5% | |
| 4.7 | 6 | 0.5% | |
| 4.6 | 57 | 4.4% |
| Distinct | 400 |
|---|---|
| Distinct (%) | 30.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| IntraEdge | 40 |
|---|---|
| McAfee | 40 |
| Novetta | 40 |
| Signature Science, LLC | 39 |
| Advance Auto Parts | 39 |
| Other values (395) |
| Value | Count | Frequency (%) | |
| IntraEdge | 40 | 3.1% | |
| McAfee | 40 | 3.1% | |
| Novetta | 40 | 3.1% | |
| Signature Science, LLC | 39 | 3.0% | |
| Advance Auto Parts | 39 | 3.0% | |
| Avomeen | 39 | 3.0% | |
| The Rector & Visitors of the University of Virginia | 38 | 2.9% | |
| Booz Allen Hamilton | 38 | 2.9% | |
| AAA The Auto Club Group | 38 | 2.9% | |
| Johns Hopkins University Applied Physics Laboratory | 38 | 2.9% | |
| Other values (390) | 907 | 70.0% |
Unique
| Unique | 237 ? |
|---|---|
| Unique (%) | 18.3% |
Length
| Max length | 52 |
|---|---|
| Median length | 15 |
| Mean length | 17.53240741 |
| Min length | 3 |
| Distinct | 198 |
|---|---|
| Distinct (%) | 15.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| San Jose, CA | 87 |
|---|---|
| New York, NY | 67 |
| Chicago, IL | 56 |
| Washington, DC | 52 |
| Ann Arbor, MI | 45 |
| Other values (193) |
| Value | Count | Frequency (%) | |
| San Jose, CA | 87 | 6.7% | |
| New York, NY | 67 | 5.2% | |
| Chicago, IL | 56 | 4.3% | |
| Washington, DC | 52 | 4.0% | |
| Ann Arbor, MI | 45 | 3.5% | |
| Baltimore, MD | 43 | 3.3% | |
| Raleigh, NC | 43 | 3.3% | |
| Redmond, WA | 43 | 3.3% | |
| Herndon, VA | 41 | 3.2% | |
| Phoenix, AZ | 40 | 3.1% | |
| Other values (188) | 779 | 60.1% |
Unique
| Unique | 83 ? |
|---|---|
| Unique (%) | 6.4% |
Length
| Max length | 33 |
|---|---|
| Median length | 12 |
| Mean length | 12.94367284 |
| Min length | 8 |
location_state
Categorical
| Distinct | 34 |
|---|---|
| Distinct (%) | 2.6% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| CA | |
|---|---|
| MD | |
| VA | |
| NY | |
| IL | |
| Other values (29) |
| Value | Count | Frequency (%) | |
| CA | 227 | 17.5% | |
| MD | 150 | 11.6% | |
| VA | 148 | 11.4% | |
| NY | 73 | 5.6% | |
| IL | 64 | 4.9% | |
| TX | 61 | 4.7% | |
| WA | 60 | 4.6% | |
| MI | 52 | 4.0% | |
| DC | 52 | 4.0% | |
| PA | 50 | 3.9% | |
| Other values (24) | 359 | 27.7% |
Unique
| Unique | 5 ? |
|---|---|
| Unique (%) | 0.4% |
Length
| Max length | 3 |
|---|---|
| Median length | 3 |
| Mean length | 3 |
| Min length | 3 |
Size
Categorical
| Distinct | 8 |
|---|---|
| Distinct (%) | 0.6% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| 10000+ Employees | |
|---|---|
| 501 to 1000 Employees | |
| 51 to 200 Employees | |
| 1001 to 5000 Employees | |
| 5001 to 10000 Employees | |
| Other values (3) |
| Value | Count | Frequency (%) | |
| 10000+ Employees | 457 | 35.3% | |
| 501 to 1000 Employees | 190 | 14.7% | |
| 51 to 200 Employees | 160 | 12.3% | |
| 1001 to 5000 Employees | 156 | 12.0% | |
| 5001 to 10000 Employees | 155 | 12.0% | |
| 201 to 500 Employees | 99 | 7.6% | |
| 1 to 50 Employees | 77 | 5.9% | |
| Unknown | 2 | 0.2% |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Length
| Max length | 23 |
|---|---|
| Median length | 19 |
| Mean length | 19.01388889 |
| Min length | 7 |
Founded
Real number (ℝ)
| Distinct | 119 |
|---|---|
| Distinct (%) | 9.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1840.645062 |
|---|---|
| Minimum | -1 |
| Maximum | 2019 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 10.1 KiB |
Quantile statistics
| Minimum | -1 |
|---|---|
| 5-th percentile | -1 |
| Q1 | 1932 |
| median | 1974 |
| Q3 | 2002 |
| 95-th percentile | 2012 |
| Maximum | 2019 |
| Range | 2020 |
| Interquartile range (IQR) | 70 |
Descriptive statistics
| Standard deviation | 468.824964 |
|---|---|
| Coefficient of variation (CV) | 0.2547068817 |
| Kurtosis | 11.22604673 |
| Mean | 1840.645062 |
| Median Absolute Deviation (MAD) | 30 |
| Skewness | -3.588441538 |
| Sum | 2385476 |
| Variance | 219796.8469 |
| Monotocity | Not monotonic |
| Value | Count | Frequency (%) | |
| -1 | 77 | 5.9% | |
| 1998 | 55 | 4.2% | |
| 2002 | 52 | 4.0% | |
| 2012 | 50 | 3.9% | |
| 2004 | 48 | 3.7% | |
| 2010 | 46 | 3.5% | |
| 1968 | 44 | 3.4% | |
| 1987 | 44 | 3.4% | |
| 1974 | 43 | 3.3% | |
| 1942 | 39 | 3.0% | |
| Other values (109) | 798 | 61.6% |
| Value | Count | Frequency (%) | |
| -1 | 77 | 5.9% | |
| 1625 | 38 | 2.9% | |
| 1682 | 1 | 0.1% | |
| 1740 | 1 | 0.1% | |
| 1782 | 3 | 0.2% |
| Value | Count | Frequency (%) | |
| 2019 | 2 | 0.2% | |
| 2018 | 7 | 0.5% | |
| 2017 | 6 | 0.5% | |
| 2016 | 2 | 0.2% | |
| 2015 | 7 | 0.5% |
age
Real number (ℝ)
| Distinct | 119 |
|---|---|
| Distinct (%) | 9.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 59.22067901 |
|---|---|
| Minimum | -1 |
| Maximum | 395 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 10.1 KiB |
Quantile statistics
| Minimum | -1 |
|---|---|
| 5-th percentile | -1 |
| Q1 | 16 |
| median | 36 |
| Q3 | 72 |
| 95-th percentile | 201 |
| Maximum | 395 |
| Range | 396 |
| Interquartile range (IQR) | 56 |
Descriptive statistics
| Standard deviation | 74.97659293 |
|---|---|
| Coefficient of variation (CV) | 1.26605426 |
| Kurtosis | 9.688628733 |
| Mean | 59.22067901 |
| Median Absolute Deviation (MAD) | 26 |
| Skewness | 2.898583831 |
| Sum | 76750 |
| Variance | 5621.489487 |
| Monotocity | Not monotonic |
| Value | Count | Frequency (%) | |
| -1 | 77 | 5.9% | |
| 22 | 55 | 4.2% | |
| 18 | 52 | 4.0% | |
| 8 | 50 | 3.9% | |
| 16 | 48 | 3.7% | |
| 10 | 46 | 3.5% | |
| 33 | 44 | 3.4% | |
| 52 | 44 | 3.4% | |
| 46 | 43 | 3.3% | |
| 118 | 39 | 3.0% | |
| Other values (109) | 798 | 61.6% |
| Value | Count | Frequency (%) | |
| -1 | 77 | 5.9% | |
| 1 | 2 | 0.2% | |
| 2 | 7 | 0.5% | |
| 3 | 6 | 0.5% | |
| 4 | 2 | 0.2% |
| Value | Count | Frequency (%) | |
| 395 | 38 | 2.9% | |
| 338 | 1 | 0.1% | |
| 280 | 1 | 0.1% | |
| 238 | 3 | 0.2% | |
| 203 | 1 | 0.1% |
Type of ownership
Categorical
| Distinct | 10 |
|---|---|
| Distinct (%) | 0.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| Company - Private | |
|---|---|
| Company - Public | |
| Nonprofit Organization | |
| Subsidiary or Business Segment | 61 |
| Government | 59 |
| Other values (5) |
| Value | Count | Frequency (%) | |
| Company - Private | 646 | 49.8% | |
| Company - Public | 391 | 30.2% | |
| Nonprofit Organization | 74 | 5.7% | |
| Subsidiary or Business Segment | 61 | 4.7% | |
| Government | 59 | 4.6% | |
| College / University | 52 | 4.0% | |
| Other Organization | 4 | 0.3% | |
| Hospital | 4 | 0.3% | |
| Private Practice / Firm | 3 | 0.2% | |
| Contract | 2 | 0.2% |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Length
| Max length | 30 |
|---|---|
| Median length | 17 |
| Mean length | 17.37268519 |
| Min length | 8 |
| Distinct | 65 |
|---|---|
| Distinct (%) | 5.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| Consulting | |
|---|---|
| IT Services | |
| Aerospace & Defense | |
| Computer Hardware & Software | |
| Enterprise Software & Network Solutions | |
| Other values (60) |
| Value | Count | Frequency (%) | |
| Consulting | 154 | 11.9% | |
| IT Services | 127 | 9.8% | |
| Aerospace & Defense | 118 | 9.1% | |
| Computer Hardware & Software | 106 | 8.2% | |
| Enterprise Software & Network Solutions | 77 | 5.9% | |
| Internet | 66 | 5.1% | |
| Colleges & Universities | 53 | 4.1% | |
| Research & Development | 51 | 3.9% | |
| Electrical & Electronic Manufacturing | 44 | 3.4% | |
| Insurance Agencies & Brokerages | 40 | 3.1% | |
| Other values (55) | 460 | 35.5% |
Unique
| Unique | 14 ? |
|---|---|
| Unique (%) | 1.1% |
Length
| Max length | 40 |
|---|---|
| Median length | 21 |
| Mean length | 20.92592593 |
| Min length | 2 |
| Distinct | 24 |
|---|---|
| Distinct (%) | 1.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| Information Technology | |
|---|---|
| Business Services | |
| Aerospace & Defense | |
| Retail | |
| Manufacturing | |
| Other values (19) |
| Value | Count | Frequency (%) | |
| Information Technology | 376 | 29.0% | |
| Business Services | 239 | 18.4% | |
| Aerospace & Defense | 118 | 9.1% | |
| Retail | 83 | 6.4% | |
| Manufacturing | 78 | 6.0% | |
| Insurance | 60 | 4.6% | |
| Government | 59 | 4.6% | |
| Finance | 58 | 4.5% | |
| Oil, Gas, Energy & Utilities | 55 | 4.2% | |
| Education | 54 | 4.2% | |
| Other values (14) | 116 | 9.0% |
Unique
| Unique | 2 ? |
|---|---|
| Unique (%) | 0.2% |
Length
| Max length | 34 |
|---|---|
| Median length | 17 |
| Mean length | 16.56790123 |
| Min length | 2 |
Revenue
Categorical
| Distinct | 13 |
|---|---|
| Distinct (%) | 1.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 10.1 KiB |
| $10+ billion (USD) | |
|---|---|
| $100 to $500 million (USD) | |
| Unknown / Non-Applicable | |
| $5 to $10 billion (USD) | |
| $50 to $100 million (USD) | |
| Other values (8) |
| Value | Count | Frequency (%) | |
| $10+ billion (USD) | 200 | 15.4% | |
| $100 to $500 million (USD) | 196 | 15.1% | |
| Unknown / Non-Applicable | 141 | 10.9% | |
| $5 to $10 billion (USD) | 140 | 10.8% | |
| $50 to $100 million (USD) | 118 | 9.1% | |
| $1 to $2 billion (USD) | 111 | 8.6% | |
| $2 to $5 billion (USD) | 82 | 6.3% | |
| $500 million to $1 billion (USD) | 76 | 5.9% | |
| $25 to $50 million (USD) | 75 | 5.8% | |
| $10 to $25 million (USD) | 73 | 5.6% | |
| Other values (3) | 84 | 6.5% |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Length
| Max length | 32 |
|---|---|
| Median length | 24 |
| Mean length | 23.60030864 |
| Min length | 18 |
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.First rows
| Job Title | simplified_title | seniority | Salary Estimate | min_salary | max_salary | avg_salary | hourly | employer_provided_salary | Job Description | description_length | contains_python | contains_R | contains_big_data | contains_MS | Rating | Company Name | Location | location_state | Size | Founded | age | Type of ownership | Industry | Sector | Revenue | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Data Scientist Virtual Hiring Event | Data Scientist | na | $80K-$133K\n(Glassdoor est.) | 80 | 133 | 106.5 | 0 | 0 | Aveshka Hiring Event! Data Scientist\n\nEvent Details\nDate: Friday, October 2, 2020\n\nWhat We're Hiring For\n\nData Scientist\n\nIntake Details:\n\nRequirements\n\nData Visualization\n\nBig Data\n\nProgramming\n\nWhat to bring to this event\n\nUpdated resume\n\nWhat to wear\n\nDress code is Casual (come as you are, but please be presentable).\n\nAbout Aveshka\n\nAveshka is a professional services firm that helps clients by developing creative yet highly effective solutions to today’s ever-increasing threats and challenges. Our name, derived from the Hindi word meaning “innovation” or “discovery,” reflects our drive to bring cutting-edge, breakthrough solutions to the table. Our clients appreciate our team’s thought leadership, candid advice, and genuine partnership.\n\nWhat is a Virtual Hiring Event?\nVirtual hiring events are a great way for employers and jobseekers to connect, even if they aren't in the same physical location. Hiring is a human process, and they would like to talk with you online (either through chat, on the phone, or video) to see if you’re a fit!\n\nResponsibilities\n\n•Handles raw data (e.g., structured, unstructured and mixed datasets), and analyzes data through the application of various statistical techniques or tools.\n\n•Familiar with programming languages such as, but not limited to, R, SAS, Python, MatLab, SQL, Hive, Pig, and Spark.\n\n•Experienced in working with and exploiting big data; distributed computing; predictive modeling; mathematics; statistics; machine learning; story-telling; and visualization.\n\n•Demonstrates ability to extract meaning from and interpret data using a variety of tools and methods from statistics and machine learning.\n\n•Ability to collect, clean, and mung data\n\nin a timely manner as part of a cross-functional team in an intelligence, or related environment.\n\n•Possesses strong working knowledge of the\n\nMicrosoft Office Suite, including Access, Excel, PowerPoint, Project, Visio, and Word.\n\nRequired\n\nExperience:\n\n•1-10 years of related experience\n\n•Experience with programming languages such as, but not limited to: R, SAS, Python, MatLab, SQL, Hive, Pig, and Spark.\n\n•Experience with using the Microsoft Office suite, including Access, Excel, PowerPoint, Project, Visio, and Word\n\nRequired Education:\n\n•Bachelor’s Degree | 2271 | 1 | 0 | 1 | 0 | 3.6 | Aveshka\n | Washington, DC | DC | 51 to 200 Employees | 2010 | 10 | Company - Public | IT Services | Information Technology | $10 to $25 million (USD) |
| 1 | Data Scientist Virtual Hiring Event | Data Scientist | na | $80K-$132K\n(Glassdoor est.) | 80 | 132 | 106.0 | 0 | 0 | Oasis Systems Hiring Event!\n\nEvent Details\nDate: Wednesday, September 30, 2020\n\nWhat We're Hiring For\n\nData Scientist\n\nData Analytics Project Manager\n\nIntake Details:\n\nRequirements\n\nSAS, Data Risk Analyst\n\nTechnical requirements\n\nThe interview will take place on Indeed's virtual interviewing platform. After RSVP, you will find a link in your email that will lead you directly to the video interview lobby during the event. Try to find a quiet place with good lighting and a stable internet connection.\n\nWhat to bring to this event\n\nUpdated resume\n\nCompleting our online application prior to the event is strongly encouraged and will speed up the process.\n\nWhat to wear\n\nDress code is Casual (come as you are, but please be presentable).\n\nAbout Oasis Systems, LLC\n\nOasis Systems is a leading technology services company providing a broad range of capabilities in Systems Engineering, Enterprise Systems and Applications, Information Technology, Cyber Security, Specialized Engineering Solutions, Human Factors Engineering, and Professional Services. Oasis creates sustainable value for mission critical programs with all Department of Defense Branches, FAA, NRC and other Federal Agencies. With people in 36 states and 10 countries Oasis delivers talent, innovation and intelligence for mission success.\n\nPlease Visit Our Page for more information!\nhttps://www.oasissystems.com/\n\nWhat is a Virtual Hiring Event?\nVirtual hiring events are a great way for employers and jobseekers to connect, even if they aren't in the same physical location. Hiring is a human process, and they would like to talk with you online (either through chat, on the phone, or video) to see if you’re a fit!\n\nThe successful candidate shall provide support in data analytics (including descriptive and predictive analytics, data mining, and market risk analysis), large data manipulation, data visualization and use of data analytic tools. Activities which the contractor may be tasked to perform include gathering requirements from stakeholders, conducting financial data analysis and risk analysis in a Big Data environment, and creating interactive dashboard reports and documentations.\n\nA minimum of 8 years of relevant experience in the data analysis field and a minimum of 5 years of industrial analytics experience using statistical program languages such as SAS, R, and Python (recent use during the past 3 years) as well as extensive experience with SQL.\n\nhttps://oasiscareers-oasissystems.icims.com/jobs/9890/data-scientist-risk-analyst/job | 2525 | 1 | 0 | 1 | 0 | 3.7 | Oasis Systems, LLC\n | Washington, DC | DC | 1001 to 5000 Employees | 1997 | 23 | Company - Private | IT Services | Information Technology | $100 to $500 million (USD) |
| 2 | Data Scientist Virtual Hiring Event | Data Scientist | na | $81K-$135K\n(Glassdoor est.) | 81 | 135 | 108.0 | 0 | 0 | LMI Hiring Event!\n\nEvent Details\nDate: Wednesday, September 30, 2020\n\nWhat We're Hiring For\n\nData Engineer\n\nData Scientist\n\nSoftware Engineer\n\nNetwork Engineer\n\nInformation Security Analyst\n\nIntake Details:\n\nRequirements\n\nActive US Secret Clearance (or above)\n\nTechnical requirements\n\nThe interview will take place on Indeed’s virtual interviewing platform. After RSVP, you will find a link in your email that will lead you directly to the virtual interview lobby during the event. Try to find a quiet place with good lighting and a stable internet connection.\n\nWhat to bring to this event\n\nAn electronic copy of your resume\n\nCompleting our online application prior to the event is strongly encouraged and will speed up the process.\n\nWhat to wear\n\nDress code is Casual (come as you are, but please be presentable).\n\nAbout LMI\n\nLMI is a consultancy dedicated to powering a future-ready, high-performing government, drawing from expertise in digital and analytic solutions, logistics, and management advisory services. We deliver integrated capabilities that incorporate emerging technologies and are tailored to customers' unique mission needs, backed by objective research and data analysis. Founded in 1961 to help the Department of Defense resolve complex logistics management challenges, LMI continues to enable growth and transformation, enhance operational readiness and resiliency, and ensure mission success for federal civilian and defense agencies.\n\nWhat is a Virtual Hiring Event?\nVirtual hiring events are a great way for employers and jobseekers to connect, even if they aren't in the same physical location. Hiring is a human process, and they would like to talk with you online (either through chat, on the phone, or video) to see if you’re a fit!\n\nActive Secret clearance or higher\nBachelor’s degree in data science, mathematics, statistics, economics, computer science, engineering, or a related business or quantitative discipline\nExperience working with tools, including object-oriented programming (Python, Java), computational analysis tools (R, MATLAB), and associated data science libraries (scikit-learn)\nExperience creating meaningful data visualizations and interactive dashboards using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js to communicate findings and relate them back to how your insights create business impact\nWorking knowledge of databases and SQL; preferred qualifications include linking analytic and data visualization products to database connections\nAt least 5–10 years of experience in the field | 2562 | 1 | 0 | 0 | 0 | 4.2 | LMI\n | Baltimore, MD | MD | 1001 to 5000 Employees | 1961 | 59 | Nonprofit Organization | Consulting | Business Services | $100 to $500 million (USD) |
| 3 | Sr. Manager, Supply Chain Business Intelligence and Data Science | Other | Senior | $66K-$115K\n(Glassdoor est.) | 66 | 115 | 90.5 | 0 | 0 | At Niagara, we’re looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water.\n\nConsider applying here, if you want to:\n\nWork in an entrepreneurial and dynamic environment with a chance to make an impact.\nDevelop lasting relationships with great people.\nHave the opportunity to build a satisfying career.\n\nWe offer competitive compensation and benefits packages for our Team Members.\n\nSr. Manager, Supply Chain Business Intelligence and Data Science\n\nThe Supply Chain Business Intelligence (BI) team owns data visibility and insights initiatives within the Supply Chain department. BI, together with Continuous Improvement (CI) and Training teams makes up the recently established “Supply Chain Solutions” team. This team plays a central role in defining the future of how Niagara’s Supply Chain department will operate and whether the company itself will be able to maintain a competitive advantage in our market space. The BI team support all Supply Chain functions: Planning, Procurement, Logistics, and Customer Service.\n\nThe Senior Manager of Supply Chain Business Intelligence is a Supply Chain leader who understands data from both operational/strategic points of view and is responsible for providing “Data-to-Insight” (BI) tools to support and enhance business strategies. Said leader will act as the main conduit between Supply Chain and IT as well as collaborate with other BI units housed within Finance/ Manufacturing/ Engineering. As such, s/he will be responsible for developing a roadmap and portfolio of all B.I. and technology projects necessary to support the long-term competitive needs of the entire supply chain department as well as the company as a whole. This individual will lead a team of business intelligence analysts who own the end to end for implementing data marts, ad-hoc self-serve reports, and dashboards to empower the broader group of business users.\n\nFurthermore, Data Science will be an integral part of this role. As an organization, we are very keen on exploration in this area and leveraging it to perpetuate our competitive advantage in the coming decade. With this backdrop in mind, we seeking a candidate who has significant hands-on experience working on “Data Insight” type initiative where Data Science concepts were rigorously applied within a framework of best-of-breed Data Science toolsets. This is in addition to and not in lieu of the more traditional BI responsibilities and demonstrated leadership skillset that were laid out in the proceeding segment.\n\nEssential Functions\n\nServes as a key point of contact for all data visibility and insights initiatives within the Supply Chain department and supports initiatives undertaken by cross-functional process improvement teams.\nCoordinates with Supply Chain leadership and develops BI technology and Data Science capability roadmaps for all Supply Chain functions; primary partners include: Logistics, Customer Service, Procurement, Strategic Planning, as well as non-Supply Chain functional partners such as Finance/IT.\nInjects direct Data Science know-how into the organization, including skillset and experience working within a robust Data Science platform such as Amazon SageMaker and RapidMiner.\nEnsures that the necessary data architecture and software tools are available to allow for insightful and impactful machine learning, big data, and statistical analyses.\nLeads the development of various predictive analytics/optimization/heuristics based models.\nEmploys data mining, data warehousing, segmentation, and other analytical techniques to capture important trends and create relevant measurement dashboards in platforms such as IBM Cognos, Tableau, Informatica, and Oracle OBIEE/OACS.\nUnderstands the functional and technical design/architecture of ERP/OTM/WMS/EDI technologies.\nMaintains continued enhancements and augmentations to existing B.I. tools and supply chain technology solutions.\nMonitors and manages data issues and establish plans for ensuring data quality and integrity between transaction source systems and reporting environments.\nSpearheads the development of policies, processes, standards, and best practices in data and integration management.\nDevelops and executes a strategy to provision business users with very accessible daily technical support answering analytical & technology related questions.\nPublishes periodic updates on status of various initiatives to all Supply Chain team members and key stakeholders in other departments.\nCollaborates with Continuous Improvement team to re-engineer processes, software enhancements, and KPIs framework to fully leverage our ever advancing BI capabilities.\nCollaborates with Supply Chain Training team and Supply Chain leaders to administer appropriate trainings necessary to standardize technology usage.\n\nPlease note this job description is not designed to contain a comprehensive list of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without prior notice.\n\nQualifications\n\nMinimum Qualifications:\n6 Years – Experience in Technology Consulting or Data Analytics\n6 Years – Experience in or supporting Operations/Strategy\n4 Years – Experience managing people and projects\nexperience may include a combination of work experience and education\nPreferred Qualifications:\n10+ Years– Experience in Technology Consulting or Data Analytics\n10+ Years – Experience in or supporting Operations/Strategy\n6 Years – Experience managing people and projects\nexperience may include a combination of work experience and education\nCompetencies\n\nStrong analytical and problem solving skills\nSelf-motivated with a proven record of taking the initiative\nAbility to adjust and execute in a very dynamic and ever-changing environment\nAbility to excel and deliver results working cross-functionally in a matrix environment\nTechnology acumen – Strong knowledge of latest Supply Chain integration technologies such as EDI, Web Services, Block Chain and etc.\nSoftware skills – Subject Matter Expert level knowledge/experience in enterprise systems such as Oracle EBS, JDA, Logility\nLeadership – Displays passion and optimism; Inspires and motivates others to perform well; Influences actions and opinions of others\nPeople Management and Development – Fosters a quality focus in others; Builds upon areas of strength; Designs and executes plan to improve areas of weakness\nChange Management – Communicates changes, builds commitment, and overcomes resistance\nOral Communication – Speaks clearly and persuasively in both positive and negative situations; Demonstrates ability to communicate well with other team members and with non-technical end users; Demonstrates refined and comprehensive presentation skills\nWritten Communication – Writes clearly and informatively; Presents numerical data effectively; Able to read and interpret intricate written information and data\n\nThis position embodies the values of Niagara’s LIFE competency model, focusing on the following key drivers of success:\n\nLead Like an Owner\nProvides strategic input and oversight to departmental projects\nSkilled in reducing costs and managing timelines while prioritizing long run impact\nLeads/facilitates discussions to get positive outcomes for the customer\nMakes strategic and sustainable data driven decisions which prioritize the needs of the customer over departmental/individual goals\nInnovACT\nContinuously evaluates existing programs and processes, and develops new initiatives to increase efficiency and reduce waste\nCreates, monitors, and responds to departmental performance metrics to drive continuous improvement\nCommunicates a clear vision, organizes resources effectively, and adjusts the strategy as needed when managing change\nFind a Way\nDemonstrates ability to think analytically and synthesize complex information\nEffectively delegates technical tasks to subordinates\nWorks effectively with depts, vendors, and customers to achieve organizational success\nIdentifies opportunities for collaboration in strategic ways\nEmpowered to be Great\nEngages in long term talent planning\nProvides opportunities for the development of all direct reports\nUnderstands, identifies, and addresses conflict within own team and between teams\n\nEducation\n\nMinimum Required:\nBachelor's Degree in Supply Chain/Information Technology/Business Analytics/Systems Engineering/Data Science or other related field\nPreferred:\nMaster's Degree in Supply Chain/Information Technology/Business Analytics/Systems Engineering/Data Science or other related field\n\nCertification/License:\n\nRequired: N/A\nPreferred: APICS CPIM/CSCP, PMP PMI\n\nForeign Language\n\nRequired: None Required\nPreferred: None Required\n\nAny employment agency, person or entity that submits a résumé into this career site or to a hiring manager does so with the understanding that the applicant's résumé will become the property of Niagara Bottling, LLC. Niagara Bottling, LLC will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.\n\nEmployment agencies that have fee agreements with Niagara Bottling, LLC and have been engaged on a search shall submit résumé to the designated Niagara Bottling, LLC recruiter or, upon authorization, submit résumé into this career site to be eligible for placement fees. | 9466 | 0 | 0 | 1 | 1 | 3.6 | Niagara Bottling\n | Diamond Bar, CA | CA | 1001 to 5000 Employees | 1963 | 57 | Company - Private | Food & Beverage Manufacturing | Manufacturing | Unknown / Non-Applicable |
| 4 | Manager of Data Science | Other | Senior | $37K-$76K\n(Glassdoor est.) | 37 | 76 | 56.5 | 0 | 0 | At Niagara, we’re looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water.\n\nConsider applying here, if you want to:\n\nWork in an entrepreneurial and dynamic environment with a chance to make an impact.\nDevelop lasting relationships with great people.\nHave the opportunity to build a satisfying career.\n\nWe offer competitive compensation and benefits packages for our Team Members.\n\nManager of Data Science\n\nOur growing Business Intelligence team, is responsible for Niagara’s manufacturing data insights, aptitude, and system solutions as an integral part of driving business growth and improvement. As part of this team, the Manager of Data Science is responsible for establishing and leading a world-class data science team, by leveraging analytic insights to inform business decisions and improve business strategies. Data science responsibilities primarily focus on our comprehensive manufacturing operations, as well as cross-functional initiatives with IT, Supply Chain, Engineering, Finance, and Asset Management.\n\nThe Manager of Data Science is responsible for effectively building, developing and engaging a team of manufacturing BI and data science analysts, while also serving as a broader organizational leader. The leader of data science proactively works with business executives and various key stakeholders across the business to provide advanced data modeling systems, design & launch innovative complex models, utilizing modern and traditional techniques/methodologies. The manager of data science serves as an essential part of Niagara’s long-term strategy and vision by delivering business solutions based on analytic insights.\n\nEssential Functions\n\nLeveraging a “hands-on” approach, oversee all manufacturing business intelligence and data science activities ensuring alignment with departmental and business-wide vision and strategies.\nGenerate value through data science; create and implement the data science strategy/roadmap in alignment with our company strategy, linking data-related activities to business results.\nWork in coordination with business stakeholders to proactively identify and address priority business questions.\nBuild the business’s data science competency and talent needs through role definition, and development of a team of data scientists.\nDrive business analytics and capabilities; answering key business questions using innovative analytic and data science techniques.\nDriving operational excellence; managing team productivity and quality of deliverables. Ensure consistent adoption of standards, processes and methodologies.\nDesigns, develops and implements a broad array of business analytics that solve complex problems. Identifies new opportunities to further leverage analytics, data and analytical tools.\nEnsures best practice adoption within stated areas of responsibility, applying appropriate levels of technical capability, standardization and subject matter expertise.\nProactively manages static BI reporting and ad hoc analytics requests, ensuring consistent quality and timeliness in delivery to business stakeholders.\nDrive education and evangelization of data sciences throughout the business by communicating the vision and use cases of advanced analytics.\nWorks closely with other data and analytics teams, inclusive of data analytics, data warehousing, and data engineering teams in creating big data applications through the utilization of structured and unstructured data, designing optimal data architecture, and experimenting on new machine learning techniques.\nMonitor trends in key business KPIs, providing valuable insights to relevant departments for overall business performance improvement.\nCollaborate with external data and analytics partners. Lead the development and design of the departmental vision, capabilities, infrastructure, and roadmap of data sciences capabilities.\nPlease note this job description is not designed to contain a comprehensive list of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without prior notice.\n\nCompetencies\n\nExperience with scripting languages (R, Python, SQL, Java, etc.)\nExperience in various enterprise resource solution tools such as Oracle ERP, Oracle EBS, and Oracle OBIEE/OACS.\nProven strong aptitude in data visualization platforms such as Tableau, Alteryx, PowerBI, Cognos, Grafana.\nProven strong aptitude in data science platforms such as MS Azure, RapidMiner\nExperienced in Manufacturing Execution Systems / Efficiency Improvement Analysis Applications\nNew System Implementation & Administration\nA drive to learn and master new technologies and techniques.\nProficiency in Microsoft Office applications (Excel, Word, PowerPoint, and Access)\nEntrepreneurial; Initiative and resourcefulness with limited guidance.\nLeadership – Engaging, passionate, courageous leader who inspires and influences team members of all levels with humility and respect\nProject Management – Detail oriented with the ability to prioritize multiple tasks and projects and complete assignments quickly and accurately.\nProblem Solving – Identifies and resolves problems in a timely manner; gathers and analyzes information skillfully\nOral Communication - Speaks clearly and persuasively; Demonstrates ability to communicate well with other team members and with non-technical end users; demonstrates presentation skills.\nTeam Work - Balances team and individual responsibilities; contributes to building a positive team spirit; able to build morale and group commitments to goals and objectives.\nWritten Communication - Writes clearly and informatively; presents numerical data effectively\n\nQualifications\n\nMinimum Qualifications:\n4 Years – Experience in Field or similar\n2 Years – Experience managing people/projects\nexperience may include a combination of work experience and education\nPreferred Qualifications:\n6 Years – Experience in Field or similar\n4 Years – Experience managing people/projects\nexperience may include a combination of work experience and education\nEducation\n\nMinimum Required:\nBachelor's Degree (Machine learning, Computer Science, Statistics, Engineering or similar.)\nMaster's Degree (Machine learning, Computer Science, Statistics, Engineering or similar.)\n\nAny employment agency, person or entity that submits a résumé into this career site or to a hiring manager does so with the understanding that the applicant's résumé will become the property of Niagara Bottling, LLC. Niagara Bottling, LLC will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.\n\nEmployment agencies that have fee agreements with Niagara Bottling, LLC and have been engaged on a search shall submit résumé to the designated Niagara Bottling, LLC recruiter or, upon authorization, submit résumé into this career site to be eligible for placement fees. | 7030 | 1 | 0 | 1 | 1 | 3.6 | Niagara Bottling\n | Diamond Bar, CA | CA | 1001 to 5000 Employees | 1963 | 57 | Company - Private | Food & Beverage Manufacturing | Manufacturing | Unknown / Non-Applicable |
| 5 | Data Analyst | Data Analyst | na | $50K-$88K\n(Glassdoor est.) | 50 | 88 | 69.0 | 0 | 0 | Rational is growing, and we need amazing talent to join our team. If you have an entrepreneurial attitude with a deep spirit of service and killer subject expertise, we want to talk to you. We are always looking for the next great consultant to raise the bar and push Rational to be better than we were yesterday. Staying hungry, curious, and looking forward to what’s next is part of our DNA.\n\nThis Data Analyst will be part of Rational's Technology & Data Practice and supporting one of our large biotech projects. This individual will provide strategic and tactical consultation, leadership in delivering solutions, and oversight of processes and systems. The position requires solid technical foundation, domain knowledge, as well as strong verbal and written communication skills with a proven ability to clearly communicate technical information to a non-technical audience.\n\nThis is a full time position within Rational's Technology Practice. This position is not available for Visa sponsorship or C2C work.\n\nWhat you will do:\nServe as the Business Analyst subject matter expert supporting, but not limited to Commercial portfolio\nNetwork with a new and evolving IT environment, business team, and vendors to foster strong relationships and build partnerships\nUnderstand strategy and how it translates to executable programs, projects, and efforts that align with strategic goals while taking the environmental constraints and opportunities into account\nCollaborate with cross-functional professionals to deliver high-quality and innovative solutions that meet the business needs and create new opportunities\nProvide analytic support of various levels of complexity including large, multi-year, cross-functional efforts with internal and external influencing factors\nNegotiate conflicts and complex issues to an expeditious and satisfactory resolution\nWhat you will bring:\n3+ years of exposure to the orchestrating technology solutions for technical and/or Biotechnology or Pharmaceutical organizations\n3+ years of experience in the Business Analysis or equivalent role with solution delivery and process improvement supporting cross-functional implementation of IT solutions in the Biotechnology or Pharmaceutical industry\n3+ years of experience in organization financials, financial reporting\nFamiliarity with applications used in the business area such as Salesforce and Veeva\nWorking experience in SQL Server and Snowflake (preferred, but not required)\nProven knowledge of IT solutions and application management through various product cycles and evolving work environments\nDemonstrated technical understanding of application architecture to include application servers, web servers, configuration files, relational databases, and reporting applications\nAbility to proactively plan, organize, deliver with limited oversight, prioritize, and quickly adapt to changing situations\nExcellent communication skills, including the ability to interface and influence internal and external partners at multiple organization levels\nStrong interpersonal and negotiation skills, with a high degree of self-motivation and ability to work independently\nProficient in essential tools such as Power BI, Smartsheets, PowerPoint, Visio, etc.\nWho you are:\nData Lover. You know your numbers and value the metrics behind the buyer story.\nCollaborative to the Core. Demonstrated ability to work in a team environment, as a leader and member.\nWell-rounded Professional. You have amazing communication and organizational skills along with high EQ.\nProactive. You are always thinking ahead about what is best for the Client.\nAdaptable. Change happens at lightning speed; you are flexible, enjoy challenge, and get behind new ideas\nRational is a customer experience (CX) solutions firm that pairs the capabilities of a strategic consultancy with the creativity of a full-service digital agency. We design and activate compelling experiences that create strong connections between people and brands. We put humans at the center of business and partner with our clients to deliver meaningful experiences that help their customers while driving business success. Customer satisfaction at every level is our ultimate metric, and it's what drives our mindset, skillset, and company culture.\n\nIncredible people are our non-negotiable. Our experienced team of consultants spans the globe. We love what we do, and who we do it with – let’s begin our next chapter together.\n\nRational is committed to ensuring all candidates have an equal opportunity to be considered for employment. Please let us know if you need any reasonable accommodation to participate in the job application or interview process. | 4680 | 0 | 0 | 0 | 0 | 2.7 | Rational\n | Redmond, WA | WA | 201 to 500 Employees | 2009 | 11 | Company - Public | Consulting | Business Services | Unknown / Non-Applicable |
| 6 | Data Scientist Virtual Hiring Event | Data Scientist | na | $70K-$116K\n(Glassdoor est.) | 70 | 116 | 93.0 | 0 | 0 | GEODIS Hiring Event! Offers on the Spot!\n\nEvent Details\nDate: Thursday, October 1, 2020\n\nWhat We're Hiring For\n\nAccounts Payable Manager\n\nAccounts Payable Coordinator\n\nMarketing Analyst Demand & Lead Generator\n\nSr. DC Design Engineer\n\nDC Design Engineer\n\nETL Developer II\n\nData Scientist\n\nSr. Developer - MDM\n\nSr. Engineer Infrastructure Developer Operations\n\nIT Director WMS Implementation\n\nDeveloper II - .Net\n\nIntake Details:\n\nRequirements\n\nHigh School Diploma\n\nWhat to bring to this event\n\nAn electronic copy of your resume\n\nCompleting our online application prior to the event is strongly encouraged and will speed up the process.\n\nWhat to wear\n\nBusiness (business suit, tie)\n\nAbout Geodis\n\nGEODIS is a global third-party logistics provider (3PL for short) powering the supply chains of some of the top brands and manufacturers. We are over 40,000 employees strong, with locations in over 120 countries, and 70M square feet of warehousing globally.\n\nIn other words, if you’re looking for a career in a fast-growing industry (90% of Fortune 500 companies now work with 3PLs), joining GEODIS ensures you’re also with one of the fastest growing companies in the industry.\n\nWhether you are located in one of our warehouses, one of our regional offices, or from the Americas headquarters in Nashville, Tennessee, put your career on the right track – and on the map – with GEODIS.\n\nWhat is a Virtual Hiring Event?\nVirtual hiring events are a great way for employers and jobseekers to connect, even if they aren't in the same physical location. Hiring is a human process, and they would like to talk with you online (either through chat, on the phone, or video) to see if you’re a fit!\n\nThe Data Scientist ensures that the data assets of the organization are supported by its information technology architecture. The Data Scientist is responsible for developing predictive and prescriptive analytics models, creating efficient algorithms, and innovating use of data. The Data Scientist will work closely with the rest of the operations teams, IT, and internal business partners to identify, evaluate, design, and implement statistical analyses and data exploration/visualization of internal and external, structured and unstructured, public and proprietary data. | 2260 | 0 | 0 | 0 | 0 | 3.1 | Geodis\n | Brentwood, TN | TN | 10000+ Employees | 1904 | 116 | Subsidiary or Business Segment | Logistics & Supply Chain | Transportation & Logistics | $5 to $10 billion (USD) |
| 7 | Medical Lab Scientist Virtual Hiring Event | Other Scientist | na | $20-$28 Per Hour\n(Glassdoor est.) | 40 | 56 | 48.0 | 1 | 0 | DHR Health Hiring Event! Offers on the Spot!\n\nEvent Details\nDate: Friday, October 2, 2020\n\nWhat We're Hiring For\n\nCertified Nursing Assistant\n\nRegistered Nurse - Critical Care Areas\n\nRegistered Nurse - Non-Critical Care Areas\n\nMedical Lab Scientist\n\nRespiratory Therapist\n\nRadiology Technologist\n\nIntake Details:\n\nRequirements\n\nHospital/Healthcare experience preferred\n\nRelevant License/Certification dependent on position\n\nTechnical requirements\n\nAfter RSVPing, you will be sent and email with connection instructions. Please be prepared to join the virtual meeting in a quiet place from a desktop/mobile device with a speaker, microphone, and web camera. Check that your network connection is stable to help avoid time delays in your interview.\n\nWhat to bring to this event\n\nAn electronic copy of your resume\n\nAny required certifications/licenses\n\nCompleting our online application prior to the event is strongly encouraged and will speed up the process.\n\nWhat to wear\n\nDress code is Business casual (dress pants/skirt, button down/blouse, optional tie).\n\nAbout DHR Health\n\nOur MISSION is to improve the well-being of those we serve with a commitment to excellence: every patient, every encounter, every time.\n\nOur VISION is to create a world class health system to advance medicine and increase access for the communities we serve by empowering caregivers to heal through compassion, knowledge, innovation, integrated care and excellence\n\nDHR CARES\nC- Compassion\nA - Accountability\nR - Responsibility\nE - Excellence through Knowledge\nS - Safety and Social Conscience\n\nWhat is a Virtual Hiring Event?\nVirtual hiring events are a great way for employers and jobseekers to connect, even if they aren't in the same physical location. Hiring is a human process, and they would like to talk with you online (either through chat, on the phone, or video) to see if you’re a fit!\n\nPOSITION SUMMARY:\n\nProvide services to meet the needs of patients as ordered by medical staff and performed in accordance with accepted standards and practices. This individual will perform technical functions and activities in the laboratory including, maintenance, quality control and training for highly sophisticated instrumentation and laboratory equipment use of chemicals and related supplies used in the testing process. Collects and collates data for Quality Assurance studies. Coordinates/leads work team. Sets up new equipment and/or writes procedures. Oversees work of, Lab Assistants and Phlebotomists.\n\nPOSITION EDUCATION/QUALIFICATIONS:\n\nBachelor's degree in Clinical Laboratory Science or Applied Sciences (required)\nCertification as a Medical Laboratory Scientist by the American Society of Clinical Pathologists (ASCP) or equivalent specialty certification (required)\nNo experience required\n\nJOB KNOWLEDGE/EXPERIENCE:\n\nProficient knowledge of clinical laboratory process, testing and analytical procedures and techniques, and various specialized laboratory equipment of the assigned laboratory unit.\nExcellent customer service | 3020 | 0 | 0 | 0 | 0 | 3.2 | DHR Health\n | Edinburg, TX | TX | 5001 to 10000 Employees | 1997 | 23 | Hospital | Health Care Services & Hospitals | Health Care | $100 to $500 million (USD) |
| 8 | Data Scientist 1 | Data Scientist | Junior | $57K-$94K\n(Glassdoor est.) | 57 | 94 | 75.5 | 0 | 0 | At NGL, we strive to make data-driven decisions for our internal and external customers. We endeavor to utilize advanced analytic tools and processes to help NGL use data as an asset. To help advance us even further, we’re searching for a Data Scientist to join our team. The ideal candidate will be responsible for performing complex analyses, creating advanced visualizations, applying advanced predictive analytics and machine learning techniques, and structuring data in an optimal format for NGL.\n\nPerform advanced analytics using predictive modeling, machine learning, and other advanced techniques.\nBuilds large and complex information sets using both unstructured and structured data.\nProvides detailed insights to others on issues.\nUse data driven insights to recommend opportunities for growth, competitiveness, and profitability.\nBuilds creative visualizations that tell a story.\nEffectively communicate results of advanced analytics to both technical and non- technical audiences.\nRecommend and develop new metrics to advance decision making.\nProvides leadership, coaching, and/or mentoring to others.\nShare ownership of the solution deployment, testing, quality, monitoring, and operational excellence with the rest of the agile team\nParticipate in regular team and stakeholder meetings\nContinually develop skill sets and abilities to keep them relevant, current, and applicable to NGL's current and future needs.\nFollow data science development life cycle and quality assurance best practices and governance\nPerform other duties and responsibilities as needed\n\nCritical thinking, analytical, and problem solving skills; strong technical and non-technical communication (verbal, written, listening) and interpersonal skills; highly detail oriented; ability to work independently and in a team; excellent time and priority management; proven abilities to take initiative and be innovative; working knowledge of Scrum\nRequired Proficiencies:\nAbility to lead multiple projects while providing effective input and briefing senior leaders.\nStrong problem-solving abilities.\nAbility and willingness to learn and extend skills and mentor others.\nStrong oral and written communication skills.\nExperience in statistical modeling, machine learning, and other advanced techniques.\nExperience building structured and unstructured data sets together.\nExperience creating visualizations in Tableau, PowerBI, or other similar BI tool. | 2432 | 0 | 0 | 0 | 0 | 3.2 | National Guardian Life Insurance Company\n | Madison, WI | WI | 201 to 500 Employees | 1909 | 111 | Company - Private | Insurance Carriers | Insurance | $500 million to $1 billion (USD) |
| 9 | R&D Scientist, Associate | Research Scientist | Junior | $21K-$49K\n(Glassdoor est.) | 21 | 49 | 35.0 | 0 | 0 | We Improve Lives—that’s what drives us. It’s what makes us better, more innovative, more compelled to work harder. What we do is develop superior point-of-care rapid testing solutions for healthcare providers around the world; what we help create is healthier lives and communities.\nPosition Summary*: The R&D Scientist, Associate is responsible for performing experiments to develop and refine state-of-the-art assays for the detection of infectious diseases.\nDuties & Responsibilities* include but are not limited to:\n° Responsible for the preparation and application of all buffers, test lines, control lines, and other components used in Chembio diagnostic products\n\n° Analyzes data\n\n° Writes summaries and reports\n\n° Performing daily and weekly instrument calibrations as indicated\n\n° Responsible for maintaining neat and accurate batch records as either an operator or a witness during all procedures\n\n° Compliance with regulatory standards. Adherence to all OSHA compliance laws and to the requirements of the USDA and FDA\n\n° Compliance to the requirements of cGMP’s\n\n° Maintenance of equipment and work area as directed\n\n° Reporting deviations to established processes\n\nQualifications Required*:\n\n° Bachelor’s degree in a Life Science or related field\n\n° Attention to detail and proficient record keeping\n\n° Computer literate, familiar with Microsoft Office\nCOMPANY PROFILE*\nChembio Diagnostic Systems, Inc. is a public company serving the increasing global demand for rapid tests needed for the effective prevention and treatment of infectious diseases and other conditions. Located minutes off the Long Island Expressway in Medford, NY, Chembio operates a research and manufacturing facility that is registered with the US FDA.\n\nEqual Opportunity Employer – Minorities/Women/Veterans/Disability/Gender Identity/Sexual Orientation\n\nFor more information about Chembio Diagnostic Systems Inc., please visit our website.\n\nJob Type: Full-time\n\nJob Type: Full-time\n\nBenefits:\n401(k)\n401(k) matching\nDental insurance\nDisability insurance\nEmployee assistance program\nFlexible spending account\nHealth insurance\nLife insurance\nPaid time off\nReferral program\nVision insurance\nSchedule:\n8 hour shift\nDay shift\nMonday to Friday\nSupplemental Pay:\nBonus pay\nThis Company Describes Its Culture as:\nDetail-oriented -- quality and precision-focused\nInnovative -- innovative and risk-taking\nOutcome-oriented -- results-focused with strong performance culture\nBenefit Conditions:\nWaiting period may apply\nOnly full-time employees eligible\nWork Remotely:\nNo | 2546 | 0 | 0 | 0 | 0 | 2.6 | Chembio Diagnostic Systems, Inc.\n | Medford, NY | NY | 51 to 200 Employees | 1999 | 21 | Company - Public | Research & Development | Business Services | $10 to $25 million (USD) |
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| 1286 | Data Scientist | Data Scientist | na | $81K-$133K\n(Glassdoor est.) | 81 | 133 | 107.0 | 0 | 0 | The Motivate Lab is looking for a Data Scientist who can begin immediately. In order to achieve our mission of improving people’s lives, we are committed to rigorous evaluation and analysis of our data. The Data Scientist will contribute to various projects through ongoing data management and data analysis across multiple projects, and developing lab-wide data systems. This role is an exciting opportunity for a results-oriented, innovative professional within a fast-growing organization centered around applied work to support educational research and practice.\n\nAbout Motivate Lab:\nThe mission of the Motivate Lab is to improve people's lives through rigorous motivation research. Led by two professors at the University of Virginia, Motivate Lab's annual operating budget of over $2.2M is completely supported through external grants and contracts. Our current five-year strategic plan has ambitious goals of growing the size, scope, and impact of our work in education and beyond, including sports and workforce settings. The majority of work in our organization focuses on research and development activities that develop tools to infuse learning-mindset supportive practices into educational and policy contexts, with a particular focus on supporting students from traditionally underrepresented backgrounds in higher education. We utilize our rigorous methods to design translational activities, including professional development, training, and dissemination, for both researchers and practitioners. We aim to change both the fields of practice and research through our innovative and agile methods of developing evidence-based practices.\n\nResponsibilities:\n\nCurrently Motivate Lab is working on several major projects to help faculty and administrators across higher education build more motivationally-supportive learning contexts for students. Our data sets include both quantitative and qualitative data from a variety of sources, including randomized controlled trials, administrative data, student and faculty surveys, and faculty artifacts (e.g., syllabi). The Data Scientist will be responsible for management and analyses of these data.\n\nData Analysis\n\nDevelopment and utilization of data analysis protocols / frameworks.\n\nProgramming data analysis through code primarily using R (preferably) and SPSS.\n\nAnalysis of descriptive and correlational statistics by group.\n\nAnalysis of validity and reliability of quantitative measurement scales.\n\nRegression modeling and other higher-level analytical techniques (e.g., hierarchical linear modeling, structural equation modeling, propensity-score matching, latent class analysis).\n\nUsing RMarkdown (or other reporting technology) to create analytic reports for stakeholders and internal lab personnel.\n\nParticipate in the generation and delivery of insight gleaned from analyses for multiple audiences (e.g., academics, practitioners, funders, etc.)\n\nProvide recommendations to internal and external stakeholders based on research findings.\n\nCollaborate on the creation of professional development programs and materials using data.\n\nData Management\n\nCreate and manage longitudinal datasets.\n\nBuild datasets by merging from various data sources, tables, files, etc.\n\nClean datasets in preparation for analysis.\n\nCoordination of data management and analysis efforts with research coordinators and the lab’s data manager(s).\n\nCreating Lab-Wide Data Systems\n\nDirect the creation and consistent updating of data management protocols, data analysis protocols, and data translation protocols (i.e., moving from analysis to reporting and improvements in practice).\n\nSupporting the ongoing skill development of Motivate Lab undergraduates and staff.\n\nThis role may require additional responsibilities, as necessary.\n\nQualifications and Skills/Experiences:\n\nA Master's degree or terminal degree in Psychology, Public Policy, Education, Quantitative Methods, or related field is required. PhD preferred.\n\nBasic knowledge of psychological constructs, including theories of motivation and intelligence is preferred.\n\nAt least 5 years of experience in a relevant, fast-paced professional setting (including graduate research labs); past data analysis experience in education is required.\n\nStrong working knowledge of statistical research software, such as R (preferred), Stata, or SPSS.\n\nProficiency in analyzing, managing, and reporting complex quantitative and qualitative data, with specific ability to apply work in education.\n\nEffective interpersonal communication skills.\n\nStrategic thinker with advanced problem-solving skills.\n\nExcellent organizational skills with a strong understanding of systems and procedures.\n\nFierce work ethic and sense of purpose, with the ability to work well as part of a dynamic team.\n\nPhysical Demands: This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.\n\nCommitment to Justice, Diversity, Equity, and Inclusion:\n\nMotivate Lab is committed to:\n\nRecruiting talented and diverse staff.\n\nRecruitment and retention of a diverse workforce, and providing an inclusive and supportive environment in which staff and faculty are recognized as integral to the success of our work.\n\nPromoting a culture of integrity, mutual respect, excellence, collaboration and innovation.\n\nCompensation:\n\nCompetitive salary is commensurate with individual’s experience and skills. All full-time employees receive a comprehensive benefits package .\n\nApplication:\n\nMotivate Lab is an equal opportunity employer and encourages a diverse pool of candidates to apply. For questions about the position, please contact Alison Lubin , Motivate Lab Project Associate, and for questions about the application process please contact Bethany Case , Recruiter. Applicant review will begin October 5th, and new applications will be reviewed on a rolling basis and the posting will remain open until filled. This position will consider remote applicants. This role is restricted with a 1 year term limit, continuation is dependent upon the availability of funding, satisfactory performance, and the need for the role.\n\nPlease apply through Workday , and search for “ Data Scientist ". Complete an application online and attach:\n\nCover letter addressing 1) p revious experience with data management and analysis, 2) previous experience working in teams and training/managing others (if relevant), and 3) how you intend to bring a focus on diversity, equity, and inclusion to this role.\n\nCV/resume.\n\nAttach all materials into the resume submission field, multiple documents can be submitted into this one field. Alternatively, please combine all into one PDF. Internal applicants must apply through their UVA Workday profile by searching 'Find Jobs'. Applications missing materials will not be considered.\n\nThe University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information. | 7646 | 0 | 1 | 0 | 1 | 4.3 | The Rector & Visitors of the University of Virginia\n | Charlottesville, VA | VA | 10000+ Employees | 1819 | 201 | College / University | Colleges & Universities | Education | $1 to $2 billion (USD) |
| 1287 | Data Scientist | Data Scientist | na | $60K-$102K\n(Glassdoor est.) | 60 | 102 | 81.0 | 0 | 0 | Job Description\n\nRole Data Scientist\n\nKey Responsibilities Work cross functionally to define problem statements, collect data, find key insights, build analytical models and make recommendations.\n\nBuild and maintain key predictive, regression, causal, time-series, optimization & customer segmentation, capacity constraint models.\n\nLeverage tools like R, PHP, Python, Hadoop & Azure Data Bricks, ADF, ADLS, Azure Analysis Service to drive efficient analytics.\n\nCommunicate final recommendations and drive decision making.\n\nAbility to work independently or to manage a virtual team that will research innovative solutions to challenging business problems\n\nAbility to collaborate with team and drive analytic projects end to end,\n\nSuperior communication skills, both verbal and written\n\nAttention to detail and data accuracy\n\nBusiness reporting\n\nMandatory Skills · Degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research, Management Science).\n\n· Hands on experience in building machine learning models using algorithms such as K-Means, SVM, KNN, Tree-Based Methods as well as different forecasting techniques.\n\n· Industry experience in Data analytics/BI, Forecasting modeling and visualization, Optimization and statistics.\n\n· 5+ years of Scripting with one of these languages (R, PYTHON).\n\n· 5 or more years of overall IT/DBMS/Data Store experience.\n\n· Three or more years of experience in, big data, data caching, data federation and data virtualization management\n\n· Understand the internals of R and Python (Who can perform root cause analysis for the issues encountered in production)\n\n· Prior experience with cloud services or cloud data services and/or data analytics projects preferred - Platform knowledge (Azure, Windows and Linux)\n\n· Good knowledge of Cloud Architecture (Public and Private clouds) – AZURE, AWS\n\nDesired Skills · Expert in querying and analyzing big data using Hive, Python, SQL, Scope and/or C# · Experience working with unstructured big data (Hadoop and/or Cosmos)\n\n· Experts in advanced Excel functions (e.g., creating formulas, pivot tables) and PowerBI\n\n· Prior knowledge of data modelling and processing techniques for big data systems\n\n· Solid understanding of BI and data solutions, including Power-pivots, cubes, and datamarts.\n\n· Self-motivated, agile and driven to think out-of-the-box\n\n· Ability to influence diverse audiences and build strong partnerships with stakeholders\n\nTotal Experience Required 7 Years\n\nWork Location Redmond\n\nJob Function\n\nCONSULTANCY\n\nRole\n\nDeveloper\n\nJob Id\n\n161371\n\nDesired Skills\n\nAzure | Machine Learning | Python | T SQL | 2645 | 1 | 1 | 1 | 0 | 3.7 | Tata Consultancy Services (North America)\n | Redmond, WA | WA | 10000+ Employees | 1968 | 52 | Subsidiary or Business Segment | IT Services | Information Technology | $10+ billion (USD) |
| 1288 | Data Scientist | Data Scientist | na | $60K-$89K\n(Glassdoor est.) | 60 | 89 | 74.5 | 0 | 0 | Role Overview:\n\nLooking for data scientists that will help us discover and leverage digital retail data to help our clients drive top line sales and add meaningful value to their businesses. Primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated into our various platforms. In addition, applying advanced machine learning techniques where appropriately to improve performance of the Decision Science solutions.\n\nKey Accountabilities:\nOwn data science projects through full cycle implementation\nPerform analysis to predict outcomes based on business questions/problems\nProcessing, cleansing, and verifying the integrity of data used for analysis including normalization, standardization, PCA, correlation, data wrangling, etc.\nSelecting features, building and optimizing classifiers using machine learning techniques\nData mining using state-of-the-art methods including but not limited to K-means, kNN, Neural Networks, Decision Trees, Random Forests, Logistic Regression, Linear/Multiple Regression, etc\nDoing ad-hoc analysis and presenting results in a clear manner\nMarket Mix Models\nQuantify what drove sales changes looking at metrics such as Average Selling Price, Out of Stock, Coupons, Discounts, Media attributed clicks, etc.\nUtilize results to help our clients make better investment choices to drive incremental sales\nIntegrate models into our internal dashboard to visualize and make output of models easily accessible\nMedia Analytics\nParticipate in media innovation groups to test and learn new ways of setting up and running media campaigns on Amazon (AMS, AAP), and other online retailers including but not limited to Instacart, Walmart, Target, Kroger, Shipt, etc.\nDevelop and test models to move from manual and rule-based campaign management to programmatic campaign management\nHypothesis Testing\nPerform hypothesis testing to better understand data sets and comparison of data sets.\nThe following tests might include but are not limited to Normality Testing, T-Test, Chi-Square Test, ANOVA, HOV, etc.\nCoach team members less experience in the field of ML\nSkills, Experience, Qualifications Required:\nWe’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field\nExperience with programmatic media, Google ads, Facebook Advertising, etc. is a plus\nExperience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc\nExperience querying databases and using statistical computer languages: R, Python, SQL, etc. Excellence in at least R or Python is highly desirable\nExperience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.\nExperience with data visualisation tools, such as D3.js, GGplot, Tableau, etc.\nExcellent written and verbal communication skills for coordinating across teams\nWhat we offer:\nOur benefits package incorporates what we’re passionate about – unlocking your future, overall well-being, and sustainability – whilst giving you control over your benefits.\nUnlimited Paid Time Off\n401K – Saving Incentive plan\nMedical and Dental Insurance plans\nFlexible Spending Accounts\nVision benefits\nGreat learning and development opportunities\nLife Assurance and Disability insurance\nOption to opt into the Ascential Shares Scheme\nAbout Flywheel\n\nFlywheel Digital is a diverse collection of practitioners who have solved the most challenging problems for numerous Fortune 500 companies on Amazon. We love rolling up our sleeves to figure out the root cause of issues and implement structural fixes to get and keep our client's business on track. Our team of business managers, search managers, analysts, and software developers work together to provide industry-leading support to the best brands on Amazon. Flywheel are headquartered in Baltimore in the United States and have recently set up a European hub in London. In 2018 Flywheel was acquired by Ascential PLC.\n\nWant more info?\n\nFind out more on what our people say:\n\nAscential YouTube Channel\n\nIf we inspire you, why not join and inspire us? | 4312 | 1 | 1 | 1 | 1 | 3.6 | WGSN\n | Baltimore, MD | MD | 1 to 50 Employees | 1998 | 22 | Company - Private | Consulting | Business Services | $50 to $100 million (USD) |
| 1289 | Data Scientist | Data Scientist | na | $72K-$124K\n(Glassdoor est.) | 72 | 124 | 98.0 | 0 | 0 | Job Description\nThe New York City Department of Investigation (DOI) is one of the oldest law enforcement agencies in the country with a mission of combating municipal corruption. It serves the people of New York City by acting as an independent and nonpartisan watchdog for New York City government, City agencies, and City employees, vendors with City contracts, individuals and entities that receive City funds.\n\nSquad 5 seeks a Data Scientist who will support the criminal and/or policy-driven investigative activities of the Inspectors General overseeing not-for-profit organizations doing business with the City of New York, as well as multiple City agencies, including the Department of Information Technology & Telecommunication (DOITT), Department of Youth & Community Development (DYCD), and Department for the Aging (DFTA). In this role, the Data Scientist will assist and work with DOI investigators under the supervision of the Deputy Inspector General for Agency Oversight, with guidance from the Director of Data Analytics, and in collaboration with Data Analysts from other squads, in building and enhancing complex financial fraud investigations through large-scale data collection and analysis.\n\nThe Data Scientist is expected to:\n\n· Develop and enhance practices for identifying patterns and trends related to fraudulent contractor and financial activity.\n· Acquire data from primary or secondary data sources and maintain databases/data systems.\n· Develop and implement data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.\n· Conduct quality assurance of data.\n· Maintain, summarize, and report on outcomes of data analysis.\n· Work collaboratively with DOI investigators to generate investigative leads, create reports, and interpret data.\n· Work collaboratively with other law enforcement agencies and City agencies to generate investigative leads, create reports, and interpret data.\n· Visualize, communicate and present findings in a cogent manner through compelling reports to key decision-makers.\n\nThe Data Scientist will work on multi-disciplinary teams that may include investigators, attorneys, and leadership from various New York City agencies that DOI oversees. The successful Data Analyst will be conscientious, creative, detailed-oriented, self-motivated, and flexible enough to perform effectively both independently and as part of multi-disciplinary team.\n\nIf selected, the candidate will be fingerprinted and undergo a background investigation. In addition, because the position has a law enforcement and/or investigative function, the candidate's consumer credit history will be reviewed during the background investigation, as permitted by NYC Administrative Code § 8-107(24)(b)(2)(A).\nMinimum Qual Requirements\n1. A four-year high school diploma or its educational equivalent approved by a State's Department of Education or a recognized accrediting organization and four years of satisfactory full-time experience in an industrial or governmental agency in the field of investigation, auditing, law enforcement, security, inspections, or in a major operational area of the agency in which the appointment is to be made; or\nA baccalaureate degree from an accredited college or university; or\nEducation and/or experience equivalent to "1" or "2" above.\nPreferred Skills\n1. Knowledge in object oriented programming languages including Python.\nStrong analytical, written and oral communication skills;\nKnowledge in query languages and RDBMS. Oracle (PL/SQL), MS SQL Server (T-SQL), MySQL (SQL/PSM), PostgreSQL (PL/pgSQL).\nFamiliarity with data acquisition tools and techniques, including ETL, is highly preferred.\nAdvance knowledge in MS Excel or Access. VBA, DAX, Power Pivot, Power Query, ability to create Pivot Tables and complex nested formulas.\nKnowledge in analytics software (i2 Analyst Notebook, Palantir, Cognos, etc).\nDatabase related certifications from Oracle or Microsoft.\nStrong communication skills, excellent judgment, and confidence to discuss results of analysis.\nAbility to turn concepts into well-documented deliverables and insights.\nAbility to initiate and drive projects to completion with minimal supervision.\nAbility to work collaboratively in a team environment and incorporate constructive feedback to improve work product.\nHighly detail-oriented and organized with the ability to prioritize tasks appropriately and manage a pipeline of projects.\nAbility to exercise discretion on sensitive or confidential matters.\nDemonstrated interest in law enforcement, criminal justice, or social service.\nWho you are:\nYou thrive on making sense of raw data.\nYou are very well-organized and an expert with Microsoft Excel.\nYou are a curious, flexible thinker and quick learner, and are excited about learning new tools and materials.\nYou adapt easily to dynamic situations, and are flexible in managing priorities.\nYou are a self-starter and an excellent team player who communicates effectively, works well under pressure and meets deadlines.\nTo Apply\nThe City of New York is an equal opportunity employer and is strongly committed to a policy of non-discrimination. We are committed to recruiting a diverse and inclusive talent pool.\n\nAll current City Employees may apply by going to Employee Self Service (ESS) http://cityshare/ess, Click on Recruiting Activities/Careers and Search for the specific Job ID# 423471.\nAll other applicants please go to www.nyc.gov/career/search and search for the specific Job ID# 423471.\n\nPlease do not email, mail or fax your resume to DOI directly. Submissions of resumes does not guarantee an interview. Due to the high volume of resumes DOI receives for positions, only selected candidates will be contacted.\n\nAppointments are subject to Office of Management & Budget approval for budgeted headcount.\nResidency Requirement\nNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview. | 6271 | 1 | 0 | 0 | 1 | 3.5 | City of New York\n | New York, NY | NY | 10000+ Employees | 1625 | 395 | Government | Municipal Governments | Government | Less than $1 million (USD) |
| 1290 | Analytical Chemist/Scientist for Biologics Group | Other Scientist | na | $36K-$55K\n(Glassdoor est.) | 36 | 55 | 45.5 | 0 | 0 | About the Opportunity\nAre you looking for a fast paced position in a rapidly growing company? We are seeking an Analytical Chemist/Scientist for our Biologics Group in Ann Arbor, Michigan. We are searching for talented and motivated individuals that would enjoy working in a team oriented, entrepreneurial company.\nJob Description and Responsibilities\nLearn techniques spanning across the entire spectrum of analytical chemistry from wet chemistry to HPLC, NMR, Mass Spectrometry, FTIR, GC and GC-MS\nPerform testing using a variety of technologies including HPLC, LC-MS, GC, GC/MS, Microscopy, FTIR and UV\nExecute projects in support of client needs including product deformulation and product development, failure analysis and problem solving, impurity identification, extractable and leachable studies, and structural characterization\nFollow all safety requirements including wearing appropriate personal protective equipment\nGenerate supporting laboratory documentation\nEnsure compliance with government rules and regulations (FDA, cGMP, DEA, ICH, OSHA, etc.)\nImplement new equipment and processes independently, capable of conducting appropriate qualification and validation activities\nExecute projects with minimal supervision\nHave the ability to analyze data from the qualitative to the rigorously statistical and defend conclusions based on data\nHave the ability to demonstrate strong problem-solving and analytical abilities\nRequirements\nExperience with analytical method development\nExperience with protein mass spectrometry, proteomics (LC-MS/MS or LC-QTOF)\nExperience with mammalian cell culture\nExperience working with proteins and nucleic acids\nExperience with HPLC or FPLC\nEffective scientific writer (experience with report writing)\nEffective oral presenter (experience with scientific presentations)\nEffective time management\nMust be a flexible, adaptable, self-driven team player with a positive attitude\nPreferred\nHands-on experience with AAV or lentivirus\nHands-on experience with viral transduction assays\nExperience with capillary electrophoresis\nExperience with GC-MS\nExperience with method validation\nExperience with MALDI or TOF\nExperience with QC method development/validation\nBachelor's degree (preferred)\n3-7 years’ experience\nWhy Work for Us?\nAvomeen is a full-service laboratory with unique analytical, product testing and formulation development expertise. Each member of the Avomeen team plays a critical and visible role in delivering high-quality scientific solutions, providing them with an opportunity to directly impact Avomeen’s success and advance their career. We make every effort to reward outstanding performance and provide interesting and scientifically challenging work. In order to ensure the success, development, and growth of our employees, we are committed to offering a variety of training opportunities.\nBecome Part of our Community\nWe recognize that our single greatest resource is our people, and our team members choose Avomeen not only to join our scientific knowledge-based community, but also to become part of a collaborative team committed to exemplary science and service to our clients. Successful Avomeen employees have a positive, client-centric outlook, and embody principles of integrity and leadership, as well as creativity, flexibility, and perseverance. | 3323 | 0 | 0 | 0 | 0 | 3.8 | Avomeen\n | Ann Arbor, MI | MI | 51 to 200 Employees | 2010 | 10 | Company - Private | Research & Development | Business Services | $10 to $25 million (USD) |
| 1291 | Machine Learning Engineer | Machine Learning Engineer | na | $54K-$97K\n(Glassdoor est.) | 54 | 97 | 75.5 | 0 | 0 | Machine Learning Engineer\n10835\nPhoenix, AZ\n7/13/2020 11:11:00 AM\n\nIT\nContractor - W2\n\nJob Description\nJob Description – Python/ML – Senior Engineer/ Architect\n\nSite Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space.\n\nWhat you will be doing:\nConceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach\nResearch latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability\nDevelop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering\n\n\nQualifications:\nA BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience\n5 + years of experience in Python with emphasis on machine learning\nHands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn\nExperience in designing mission critical highly available enterprise applications\nStrong knowledge of Linux internals and experience managing Linux systems in high traffic environments\nStrong knowledge of machine learning, mathematical modeling, R, and statistics\nStrong interpersonal communication skills and the ability to work well in a diverse team-focused environment\n5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred\nKnowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred\n\nJob Requirements\nJob Description – Python/ML – Senior Engineer/ Architect\n\nSite Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space.\n\nWhat you will be doing:\nConceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach\nResearch latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability\nDevelop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering\n\n\nQualifications:\nA BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience\n5 + years of experience in Python with emphasis on machine learning\nHands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn\nExperience in designing mission critical highly available enterprise applications\nStrong knowledge of Linux internals and experience managing Linux systems in high traffic environments\nStrong knowledge of machine learning, mathematical modeling, R, and statistics\nStrong interpersonal communication skills and the ability to work well in a diverse team-focused environment\n5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred\nKnowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred | 4986 | 1 | 0 | 1 | 0 | 3.8 | IntraEdge\n | Phoenix, AZ | AZ | 501 to 1000 Employees | 2002 | 18 | Company - Private | IT Services | Information Technology | $50 to $100 million (USD) |
| 1292 | Data Science Instructor | Instructor | na | $121K-$196K\n(Glassdoor est.) | 121 | 196 | 158.5 | 0 | 0 | Join our team dedicated to developing and executing innovative solutions in support of customer mission success.\n\nJob Description:\n\nNovetta is seeking a skilled Data Science Instructor to support a fast paced, innovative project supporting our client in the field of data science and AI/Machine Learning.\n\nBasic Qualifications:\nSME skill level\n15+ years of experience in data science or a related field\nAbility to become familiar with current client priorities, programs and issues in order to adapt training programs to reflect changes in client mission, structure, regulations, or processes.\nExcellent oral, written, and interpersonal communication skills\nOutstanding facilitation skills to manage group processes and elicit student participation\nAnalytic and problem-solving skills\nDemonstrated ability to apply structured analysis methods to various types of data to establish trends, determine variability, and diagnose the effect on training curricula.\nAbility to work independently and as part of a team\nSecurity Clearance:\nAn active TS/SCI w/Poly clearance\n\nNovetta, from complexity to clarity.\n\nNovetta delivers highly scalable advanced analytics and secure technology solutions to address challenges of national and global significance. Focused on mission success, Novetta pioneers disruptive technologies in machine learning, data analytics, full-spectrum cyber, cloud engineering, open source analytics, and multi-INT fusion for Defense, Intelligence Community, and Federal Law Enforcement customers. Novetta is headquartered in McLean, VA with over 1,000 employees across the U.S.\n\n\nOur culture is shaped by a commitment to our core values:\n\nIntegrity • We hold ourselves accountable to the highest standards of integrity and ethics.\n\nCustomer Success • We strive daily to exceed expectations and achieve customer mission success.\n\nEmployee Focus • We invest in our employees' professional development and training, respecting individuality, and fostering a culture of diversity and inclusion.\n\nInnovation • We know that discovering new and innovative ways to solve problems is critical to our success and makes us a great company.\n\nExcellence in Execution • We take pride in flawless execution as we build a company that is best in class.\n\n\nEarn a REFERRAL BONUS for the qualified people you know.\nFor more details or to submit a referral, visit bit.ly/NovettaReferrals.\n\nNovetta is an equal opportunity/affirmative action employer.\nAll qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. | 2702 | 0 | 0 | 0 | 0 | 4.5 | Novetta\n | Herndon, VA | VA | 501 to 1000 Employees | 2012 | 8 | Company - Private | Enterprise Software & Network Solutions | Information Technology | $100 to $500 million (USD) |
| 1293 | Data Scientist- Logistics Delivery Team | Data Scientist | na | $94K-$155K\n(Glassdoor est.) | 94 | 155 | 124.5 | 0 | 0 | Grubhub is dedicated to connecting hungry diners with our wide network of restaurants across the country. Our innovative technology, easy-to-use platforms and streamlined delivery capabilities make us an industry leader today, and in the future of online food ordering.\nWe strive to create a workplace that reflects the diversity of our customers and the communities we serve. When you join our team, you become part of a community that works together to innovate, solve problems, take risks, grow, work hard and have a ton of fun in the process!\nWhy Work For Us\nWe have a fast-paced environment and that is what our teams thrive on. Grubhub believes in empowering people and offering opportunities for development, as well as professional growth. We value strong, positive relationships in all areas: with each other, our customers and our greater community. Want to be a part of a team of diverse collaborators in an authentically fun culture? If so, we want to talk to you - and hear what’s your favorite restaurant for food delivery!\nGrubhub is looking for an innately curious, business-minded, results-oriented Data Scientist to work on our Logistics Data Science team. As part of our Delivery initiative, this team is focused on developing models, algorithms, simulations, and experiments to accelerate and perfect our delivery systems. As a member of this highly collaborative team, you will get to partner with stakeholders all across the business to solve diverse, novel and highly formidable problems. The team’s responsibilities are uniquely broad; they encompass topics such as delivery timing estimation, driver payment strategies, dynamic market balancing and smarter driver dispatching.\nA successful candidate is a motivated person with strong model, algorithm, and software development, and communication skills. They should hold themselves to a high standard for coding best practices and a passion for pushing their team to new heights by designing new tools and evangelizing durable and efficient solutions for deploying large scale machine learning models and algorithms. Ideally, the candidate would strive to remain abreast with related science technologies, show growth in charting new avenues for automation through data science and the rare ability to appropriately balance short term gains with long term goals.\n\nBuild and deploy models and algorithms that intelligently automate a diverse array of services and operations that make Grubhub food delivery possible.\nYou will constantly pivot between the daily tasks of research, model building and programming to architecting a strategic vision for how our team can automate and optimize Grubhub’s delivery operations.\nYou will develop and maintain strong relationships with software engineering teams consuming your algorithm and model outputs.\nApply robust and maintainable coding practices to ensure high-quality outputs at all times to our model consumers.\n\nYou should have:\nMaster’s degree in a quantitative or technical field such as Statistics, Mathematics, Physics, Computer Science or Computer Engineering\n4 years of industry experience in a data science role or adjacent position\nExpert knowledge with Python scripting language and SQL.\nExperience with the entire pipeline of deploying machine-learning algorithms including their development, validation, implementation, and production launch.\nDemonstrable proficiency in basic statistics, linear algebra, and calculus as they relate to machine learning concepts.\nInterest in coding best practices, both in acquiring them, developing them, and evangelizing them to teammates and others.\nStrong ability to distill and communicate complex technical concepts and solutions at a level appropriate for the intended audience.\nGot These? Even Better:\nPh.D. in aforementioned quantitative or technical field or 6 years of industry directly relevant industry experience.\nPast successes processing, research, and modeling GPS data or geotraces.\nExperience with big data: extraction, processing, filtering, and presenting large data quantities using cloud technologies like AWS.\nFamiliarity with utilizing a clustered distributed-data processing tool such as Spark, Dask or Hive.\nExpert level knowledge of experimental statistics, research and best practices.\n\nFlexible PTO. Grubhub employees are provided a generous amount of time to recharge their batteries.\nHealth and Wellness. We provide programs that support your overall well-being such as generous medical benefits, employee network groups, company-wide fitness challenges, and a comfortable and casual workplace! We also support our parents by offering 8 weeks of paid parent bonding time, a 4-week returnship program, and 6-8 weeks paid medical leave.\nLearning and Career Growth. Your personal and professional development is a priority at Grubhub. From day one, we empower you to lead and be an active participant in your career growth. We provide continuous learning opportunities, training, and coaching and mentorship programs.\nMealPerks. Who’s ready for some lunch? We provide our employees with a weekly Grubhub credit to enjoy and support local restaurants. We also offer company-wide meals several times a year to bring our Grubhub family together.\nFun. Every Grubhub office has an employee-led Culture Crew that connects people through fun, meaningful events and initiatives. Some of our popular past events include: Wing-eating contests, Grubtoberfest, 5k Runs, Bring Your Child to Work Day, regular happy hours, and more!\nSocial Impact. We believe in the importance of serving the communities that support our business. In addition, employees are given paid time off each year to support the causes that are important to them.\n\nGrubhub is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. The EEO is the Law poster is available here: DOL Poster. If you are applying for a job in the U.S. and need a reasonable accommodation for any part of the employment process, please send an e-mail to TalentAcquisition@grubhub.com and let us know the nature of your request and contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address.\n\nCA Privacy Notice: If you are a resident of the State of California and would like a copy of our CA privacy notice, please email privacy@grubhub.com. | 6553 | 1 | 0 | 1 | 1 | 3.9 | Grubhub\n | Chicago, IL | IL | 1001 to 5000 Employees | 2004 | 16 | Company - Public | Internet | Information Technology | $100 to $500 million (USD) |
| 1294 | Data Scientist | Data Scientist | na | $51K-$92K\n(Glassdoor est.) | 51 | 92 | 71.5 | 0 | 0 | Job Description\n\nJob Description Summary\n\nAdvance Auto Parts, a leader in the automotive aftermarket, currently has an opening for a Data Scientist. As a Data Scientist at Advance Auto Parts, you will have an opportunity to disrupt a $100B auto parts industry to bring better and faster solutions to customers. You will be responsible for analyzing billions of transactions to find patterns that will help improve our company and build data products to extract valuable business insights as it relates to assortment planning and inventory optimization. You will be part of an elite data science team formed to help the organization live its mission of Advancing a World in Motion.\n\nJob Description\n\nEssential Duties and Responsibilities include the following.\nIdentify and implement strategies to leverage various large data sources for purposes of improving assortment availability\nCollect, analyze, and interpret information from multiple data sources identifying actionable insights that create efficiencies and generate revenue.\nBuild predictive models and machine-learning algorithms for second-level analytics and assortment related processes\nDevelop reports and/or presentations leveraging data visualization tools that clearly and concisely communicate analytical findings and recommendations to key stakeholders.\nAnalyze customer sales, transaction, and vehicle related data to identify trends and patterns for use in improving store assortments\nFamiliarity with ANSI SQL\nConduct digital channel analysis to understand traffic and revenue drivers, both in-store and on-line. Leverage analytical tools (SQL, Python, R) and data mining techniques to perform advanced data manipulation and extract insights from large databases.\nSupport ad hoc data analysis as requested.\nDemonstrated desire for continued learning and keeping up with latest techniques in the field of statistics, predictive analytics, operations research or related focuses.\nCapable of working both independently and on team projects.\nOther duties may be assigned.\nRequired Qualifications\n\nCapable of performing the duties listed above. Proven understanding of latest modeling and forecasting techniques. Skilled with python programming techniques, unit testing, documentation. Familiarity with AWS, Notebooks, Hadoop, EMR and S3 a plus. Familiarity with agile project management a plus.\n\nEDUCATION and/or EXPERIENCE\n\nBachelors Degree in Computer Science, Mathematics, Engineering or other relevant disciplines Understanding of relational databases and experience with data mining. Minimum of 2 years of work experience in a field related to data science.\n\nPreferred Qualifications\n\nMasters Degree or PhD in Data Science or another quantitative field. | 2725 | 1 | 0 | 1 | 1 | 3.3 | Advance Auto Parts\n | Raleigh, NC | NC | 10000+ Employees | 1932 | 88 | Company - Public | Automotive Parts & Accessories Stores | Retail | $5 to $10 billion (USD) |
| 1295 | Data Scientist | Data Scientist | na | $88K-$119K\n(Glassdoor est.) | 88 | 119 | 103.5 | 0 | 0 | At Jabil, we empower the brands who empower the world – it’s our reason for being and the guiding force that’s driving us to become the most technologically advanced manufacturing solutions provider on the planet. Whether we’re serving one of the world’s biggest and best known brands or the coolest tech startups, our resolve never wavers. We share common desires with these brands: to make the world a better, safer and cleaner place.\n\nJOB QUALIFICATIONS\nKNOWLEDGE REQUIREMENTS\n\n● Advanced Statistics, operations research/ management, mathematics or business analytics with experience, courses, or project work in an analytic methods such as linear, mixed linear, constraint programming, modeling, simulation, time series analysis, pattern recognition, queuing theory, multivariate analysis, and other various predictive analytics techniques\n\n● Strong written and verbal communication skills and the ability to work effectively in teams and under pressure. Multi-lingual capability is a plus.\n\n● Ability to draw conclusions from data and prescribe actionable and measurable activities.\n\n● Highly motivated and creative, thinking “out of the box”.\n\n● Familiarity with non-relational data frameworks (aka NoSQL, eg. Hive).\n\n● Experience with Apache Pig, Spark systems.\n\n● Strong team mentality, interpersonal and communications skills\n\n● Preferred working directly with management and executives\n\nJabil, including its subsidiaries, is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identify, age, disability, genetic information, veteran status, or any other characteristic protected by law. | 1714 | 0 | 0 | 1 | 0 | 3.8 | Jabil\n | San Jose, CA | CA | 10000+ Employees | 1966 | 54 | Company - Public | Electrical & Electronic Manufacturing | Manufacturing | $10+ billion (USD) |
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| 22 | Data Scientist | Data Scientist | na | $107K-$170K\n(Glassdoor est.) | 107 | 170 | 138.5 | 0 | 0 | Job Title:\nData Scientist\n\nLocation:\nUS, California, San Jose\nRole Overview:\n\n\nLooking to have an impact? Come be a part of the change as we move into a new era at McAfee. Mission driven, both at the company and functional level, we share a passion for customers at the core. Critical, highly visible role reporting into Director of Analytics, Sr Experimentation Analyst/ Data Analyst will and will own all aspects of the product experimentation program with the goal of driving data based decisions\n\n\n\nCompany Overview\n\n\nFrom device to cloud, McAfee provides market-leading cybersecurity solutions for both business and consumers. We help businesses orchestrate cyber environments that are truly integrated, where protection, detection, and correction of security threats happen simultaneously. For consumers, McAfee secures your devices against viruses, malware, and other threats, both at home and away. We want to continue to shape the future of cybersecurity by working together to build best in class products and solutions.\n\nAbout the role:\nPartner with product, marketing and technology organizations to develop and deliver data basedbusiness insights and solutions\nUse your expert knowledge of data in our data lake and reporting databases to evaluate business opportunities, size projects, conduct analysisand prototype data solutions\nOwn end to end processof defining and publishing KPIs and metrics including getting agreement from stakeholders, validation, documentation, standardization across organization and driving automation\nHelp Increase the adoption of data solutions by educating users anddeveloping user friendly documentation\nConduct exploratory data analysis and hypothesis driven deep dives into consumer behavior and subscription data to uncover opportunities through unique insights to improve consumer experience and monetization\nConduct analysis onA/B testing data to help find winners, drive new ideas for testing and promote the use of A/B testing as a tool for decision making.\nCombine your business and technical knowledge to drive value from data utilizing a variety of methodologies like descriptive and predictive analytics, statistics ,experimentation, and business intelligence\nAct as a subject matter expert for business and engineering teams on data in our data lake and various operational databases\nAbout you:\n7+ years of experience in Business or Data Analytics\n3+ experience running, analyzing and managing A/B tests\nExperience in developing reports and dashboards utilizing industry standard BI tools ( Microstrategy or Tableau preferred)\nExpertise in presenting data and analysis at all levels in the organization\nExpert level SQL knowledge required\nKnowledge of python data analysis frameworks like pandas preferred\nKnowledge of statistical package like R preferred\nExperience with online consumer data required\nDemonstrated strong collaboration skills and ability to work cross functionally\nDemonstrated ability to effectively communicate with both technical and non-technical audience\nMaster's degree in Mathematics, Statistics, Engineering or Business\nCompany Benefits and Perks:\n\n\nWe work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.\nPension and Retirement Plans\nMedical, Dental and Vision Coverage\nPaid Time Off\nPaid Parental Leave\nSupport for Community Involvement\nWe're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.\n\nJob Type:\n\n\nExperienced Hire\n\nPrimary Location:\nUS, California, San Jose\n\nAdditional Locations: | 3906 | 1 | 1 | 0 | 1 | 3.6 | McAfee\n | San Jose, CA | CA | 5001 to 10000 Employees | 1987 | 33 | Company - Private | Computer Hardware & Software | Information Technology | $10+ billion (USD) | 40 |
| 118 | Machine Learning Engineer | Machine Learning Engineer | na | $54K-$97K\n(Glassdoor est.) | 54 | 97 | 75.5 | 0 | 0 | Machine Learning Engineer\n10835\nPhoenix, AZ\n7/13/2020 11:11:00 AM\n\nIT\nContractor - W2\n\nJob Description\nJob Description – Python/ML – Senior Engineer/ Architect\n\nSite Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space.\n\nWhat you will be doing:\nConceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach\nResearch latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability\nDevelop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering\n\n\nQualifications:\nA BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience\n5 + years of experience in Python with emphasis on machine learning\nHands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn\nExperience in designing mission critical highly available enterprise applications\nStrong knowledge of Linux internals and experience managing Linux systems in high traffic environments\nStrong knowledge of machine learning, mathematical modeling, R, and statistics\nStrong interpersonal communication skills and the ability to work well in a diverse team-focused environment\n5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred\nKnowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred\n\nJob Requirements\nJob Description – Python/ML – Senior Engineer/ Architect\n\nSite Reliability engineering portfolio consists of several mission critical americanexpress.com applications. Web engineering enterprise applications are highly available applications, maintains high (~99.999%) availability in an extremely high throughput transactional system with strict performance requirements. Primary focus of the Site Reliability Engineering team is to conceptualize, design, develop and implement observability related frameworks/common components, instrumenting observability tools for enterprise that will ensure high application reliability, scalability, availability and performance of the Web applications. Site reliability team is embarking on a transformation journey to implement “Automation first” approach in Service Delivery and Site Reliability Engineering space.\n\nWhat you will be doing:\nConceptualize and implement Machine Learning driven Site Reliability Engineering Framework/Components to improve predictive monitoring and driving SRE team’s journey towards “Automation First” approach\nResearch latest technology, concepts, conceptualize solution and develop proof of concept that will improve resiliency and performance of the production infrastructure. Design and implement innovative solution/framework that will improve software engineering velocity, infrastructure resiliency and security, and data availability\nDevelop observability related common framework components (to be leveraged by enterprise applications), define standards for configuration, monitoring, reliability and performance engineering\n\n\nQualifications:\nA BS degree in Computer Science, Computer Engineering, other Technical discipline, or equivalent work experience\n5 + years of experience in Python with emphasis on machine learning\nHands on experience with – Spark, Splunk, Pandas, Numpy, and Scikit-learn\nExperience in designing mission critical highly available enterprise applications\nStrong knowledge of Linux internals and experience managing Linux systems in high traffic environments\nStrong knowledge of machine learning, mathematical modeling, R, and statistics\nStrong interpersonal communication skills and the ability to work well in a diverse team-focused environment\n5+ years of experience with building Rest APIs, API Integration, and Web Services is preferred\nKnowledge of server-side technologies such as WebSphere, JBose, NodeJS is preferred | 4986 | 1 | 0 | 1 | 0 | 3.8 | IntraEdge\n | Phoenix, AZ | AZ | 501 to 1000 Employees | 2002 | 18 | Company - Private | IT Services | Information Technology | $50 to $100 million (USD) | 40 |
| 1 | Analytical Chemist/Scientist for Biologics Group | Other Scientist | na | $36K-$55K\n(Glassdoor est.) | 36 | 55 | 45.5 | 0 | 0 | About the Opportunity\nAre you looking for a fast paced position in a rapidly growing company? We are seeking an Analytical Chemist/Scientist for our Biologics Group in Ann Arbor, Michigan. We are searching for talented and motivated individuals that would enjoy working in a team oriented, entrepreneurial company.\nJob Description and Responsibilities\nLearn techniques spanning across the entire spectrum of analytical chemistry from wet chemistry to HPLC, NMR, Mass Spectrometry, FTIR, GC and GC-MS\nPerform testing using a variety of technologies including HPLC, LC-MS, GC, GC/MS, Microscopy, FTIR and UV\nExecute projects in support of client needs including product deformulation and product development, failure analysis and problem solving, impurity identification, extractable and leachable studies, and structural characterization\nFollow all safety requirements including wearing appropriate personal protective equipment\nGenerate supporting laboratory documentation\nEnsure compliance with government rules and regulations (FDA, cGMP, DEA, ICH, OSHA, etc.)\nImplement new equipment and processes independently, capable of conducting appropriate qualification and validation activities\nExecute projects with minimal supervision\nHave the ability to analyze data from the qualitative to the rigorously statistical and defend conclusions based on data\nHave the ability to demonstrate strong problem-solving and analytical abilities\nRequirements\nExperience with analytical method development\nExperience with protein mass spectrometry, proteomics (LC-MS/MS or LC-QTOF)\nExperience with mammalian cell culture\nExperience working with proteins and nucleic acids\nExperience with HPLC or FPLC\nEffective scientific writer (experience with report writing)\nEffective oral presenter (experience with scientific presentations)\nEffective time management\nMust be a flexible, adaptable, self-driven team player with a positive attitude\nPreferred\nHands-on experience with AAV or lentivirus\nHands-on experience with viral transduction assays\nExperience with capillary electrophoresis\nExperience with GC-MS\nExperience with method validation\nExperience with MALDI or TOF\nExperience with QC method development/validation\nBachelor's degree (preferred)\n3-7 years’ experience\nWhy Work for Us?\nAvomeen is a full-service laboratory with unique analytical, product testing and formulation development expertise. Each member of the Avomeen team plays a critical and visible role in delivering high-quality scientific solutions, providing them with an opportunity to directly impact Avomeen’s success and advance their career. We make every effort to reward outstanding performance and provide interesting and scientifically challenging work. In order to ensure the success, development, and growth of our employees, we are committed to offering a variety of training opportunities.\nBecome Part of our Community\nWe recognize that our single greatest resource is our people, and our team members choose Avomeen not only to join our scientific knowledge-based community, but also to become part of a collaborative team committed to exemplary science and service to our clients. Successful Avomeen employees have a positive, client-centric outlook, and embody principles of integrity and leadership, as well as creativity, flexibility, and perseverance. | 3323 | 0 | 0 | 0 | 0 | 3.8 | Avomeen\n | Ann Arbor, MI | MI | 51 to 200 Employees | 2010 | 10 | Company - Private | Research & Development | Business Services | $10 to $25 million (USD) | 39 |
| 13 | Data Science Instructor | Instructor | na | $121K-$196K\n(Glassdoor est.) | 121 | 196 | 158.5 | 0 | 0 | Join our team dedicated to developing and executing innovative solutions in support of customer mission success.\n\nJob Description:\n\nNovetta is seeking a skilled Data Science Instructor to support a fast paced, innovative project supporting our client in the field of data science and AI/Machine Learning.\n\nBasic Qualifications:\nSME skill level\n15+ years of experience in data science or a related field\nAbility to become familiar with current client priorities, programs and issues in order to adapt training programs to reflect changes in client mission, structure, regulations, or processes.\nExcellent oral, written, and interpersonal communication skills\nOutstanding facilitation skills to manage group processes and elicit student participation\nAnalytic and problem-solving skills\nDemonstrated ability to apply structured analysis methods to various types of data to establish trends, determine variability, and diagnose the effect on training curricula.\nAbility to work independently and as part of a team\nSecurity Clearance:\nAn active TS/SCI w/Poly clearance\n\nNovetta, from complexity to clarity.\n\nNovetta delivers highly scalable advanced analytics and secure technology solutions to address challenges of national and global significance. Focused on mission success, Novetta pioneers disruptive technologies in machine learning, data analytics, full-spectrum cyber, cloud engineering, open source analytics, and multi-INT fusion for Defense, Intelligence Community, and Federal Law Enforcement customers. Novetta is headquartered in McLean, VA with over 1,000 employees across the U.S.\n\n\nOur culture is shaped by a commitment to our core values:\n\nIntegrity • We hold ourselves accountable to the highest standards of integrity and ethics.\n\nCustomer Success • We strive daily to exceed expectations and achieve customer mission success.\n\nEmployee Focus • We invest in our employees' professional development and training, respecting individuality, and fostering a culture of diversity and inclusion.\n\nInnovation • We know that discovering new and innovative ways to solve problems is critical to our success and makes us a great company.\n\nExcellence in Execution • We take pride in flawless execution as we build a company that is best in class.\n\n\nEarn a REFERRAL BONUS for the qualified people you know.\nFor more details or to submit a referral, visit bit.ly/NovettaReferrals.\n\nNovetta is an equal opportunity/affirmative action employer.\nAll qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. | 2702 | 0 | 0 | 0 | 0 | 4.5 | Novetta\n | Herndon, VA | VA | 501 to 1000 Employees | 2012 | 8 | Company - Private | Enterprise Software & Network Solutions | Information Technology | $100 to $500 million (USD) | 39 |
| 38 | Data Scientist | Data Scientist | na | $51K-$92K\n(Glassdoor est.) | 51 | 92 | 71.5 | 0 | 0 | Job Description\n\nJob Description Summary\n\nAdvance Auto Parts, a leader in the automotive aftermarket, currently has an opening for a Data Scientist. As a Data Scientist at Advance Auto Parts, you will have an opportunity to disrupt a $100B auto parts industry to bring better and faster solutions to customers. You will be responsible for analyzing billions of transactions to find patterns that will help improve our company and build data products to extract valuable business insights as it relates to assortment planning and inventory optimization. You will be part of an elite data science team formed to help the organization live its mission of Advancing a World in Motion.\n\nJob Description\n\nEssential Duties and Responsibilities include the following.\nIdentify and implement strategies to leverage various large data sources for purposes of improving assortment availability\nCollect, analyze, and interpret information from multiple data sources identifying actionable insights that create efficiencies and generate revenue.\nBuild predictive models and machine-learning algorithms for second-level analytics and assortment related processes\nDevelop reports and/or presentations leveraging data visualization tools that clearly and concisely communicate analytical findings and recommendations to key stakeholders.\nAnalyze customer sales, transaction, and vehicle related data to identify trends and patterns for use in improving store assortments\nFamiliarity with ANSI SQL\nConduct digital channel analysis to understand traffic and revenue drivers, both in-store and on-line. Leverage analytical tools (SQL, Python, R) and data mining techniques to perform advanced data manipulation and extract insights from large databases.\nSupport ad hoc data analysis as requested.\nDemonstrated desire for continued learning and keeping up with latest techniques in the field of statistics, predictive analytics, operations research or related focuses.\nCapable of working both independently and on team projects.\nOther duties may be assigned.\nRequired Qualifications\n\nCapable of performing the duties listed above. Proven understanding of latest modeling and forecasting techniques. Skilled with python programming techniques, unit testing, documentation. Familiarity with AWS, Notebooks, Hadoop, EMR and S3 a plus. Familiarity with agile project management a plus.\n\nEDUCATION and/or EXPERIENCE\n\nBachelors Degree in Computer Science, Mathematics, Engineering or other relevant disciplines Understanding of relational databases and experience with data mining. Minimum of 2 years of work experience in a field related to data science.\n\nPreferred Qualifications\n\nMasters Degree or PhD in Data Science or another quantitative field. | 2725 | 1 | 0 | 1 | 1 | 3.3 | Advance Auto Parts\n | Raleigh, NC | NC | 10000+ Employees | 1932 | 88 | Company - Public | Automotive Parts & Accessories Stores | Retail | $5 to $10 billion (USD) | 39 |
| 53 | Data Scientist | Data Scientist | na | $65K-$109K\n(Glassdoor est.) | 65 | 109 | 87.0 | 0 | 0 | Position Purpose: The primary purpose of this position is to serve as the data scientist with a split portfolio between the Atlantic City office and the Austin chemistry group.\n\nEssential Duties and Responsibilities:\n\nPerforms data analytics, specifically data clean-up, data processing, predictive modeling, chemometric statistical modeling and analysis, multivariate data analysis, machine learning, and/or data mining, as related to scientific data.\nApplies technical skills to plan and execute assigned project work including development of computational models, programming of detection algorithms, and machine learning.\nMaintains operational capabilities of computation assets as needed by project requirements.\nLeads meetings with company clients by preparing and presenting meeting materials in meetings.\nAppropriately annotates project developed computer code through comments and user manuals.\nPresents technical results through the drafting of technical reports.\nPresents experimental results and recommended actions at internal project meetings.\nSupports business development efforts as needed by drafting technical sections of proposals, providing proposal review, assessing levels of effort required to complete proposed work, and brainstorming technical solutions to client problems.\nOther duties as assigned.\n\nRequired Knowledge, Skills & Abilities (KSA's):\n\nRequired KSA's\nAbility to plan sequence of experiments to answer complicated technical questions\nAbility to lead group of co-workers in execution of a task\nSoftware programming proficiency with Java, C, R, Python, and/or MATLAB\nWorking knowledge of statistics as it applies to scientific data\nAbility to communicate technical information to non-technical audiences\nTeam player with a positive attitude\nPreferred KSA's\nDepartment of Homeland Security Suitability\nDepartment of Defense Secret Clearance\nWorking knowledge of software development practices including Agile development and Git version control\nSufficient business knowledge to support proposal efforts\n\nEducation/Experience: Incumbent professional should have a Ph.D. or master's degree in a physical science (preferably chemistry), statistics, or data science and significant experience in computer programming, computational modeling, or software development.\n\nCertificates and Licenses: No specific certificates or licenses are required for this position.\n\nClearance: The ability to obtain a Secret clearance and Department of Homeland Security suitability is required for this position.\n\nSupervisory Responsibilities: The incumbent professional may oversee junior level staff members performing tasks.\n\nWorking Conditions/ Equipment: The incumbent professional is expected to work and/or be available during regular business hours. He/she should also generally be available via e-mail or phone during non-business hours as needed to address critical issues or emergencies. He/she may be required to travel on behalf of the company up to 25%.\n\nThe above job description is not intended to be an all-inclusive list of duties and standards of the position. Incumbents will follow any other instructions and perform any other related duties, as assigned by their supervisor. | 3210 | 1 | 0 | 0 | 1 | 3.1 | Signature Science, LLC\n | Egg Harbor Township, NJ | NJ | 51 to 200 Employees | -1 | -1 | Company - Private | Consulting | Business Services | $25 to $50 million (USD) | 39 |
| 15 | Data Scientist | Data Scientist | na | $100K-$160K\n(Glassdoor est.) | 100 | 160 | 130.0 | 0 | 0 | Do you love developing creative solutions to challenging problems?\n\nAre you passionate about providing real impact to the countrys toughest national security problems?\n\nAre you searching for engaging work with an employer that prioritizes continual innovation?\n\nIf so, we are looking for someone like you to join our team at APL.\n\nThe Large-Scale Analytics Group (QAS) develops software systems that incorporate artificial intelligence (AI) and machine learning (ML) algorithms on big data platforms and graph databases as well as visual analytics to find details hidden deep within large and complex data sets. We support multiple agencies within the US Government by applying innovative analytics to uncover activities such as epidemic hotspots, illegal activities, international trade fraud, illicit manufacturing of weapons of mass destruction, and cyber-crime. You will implement and apply computationally tractable solutions and corresponding data architectures to address the needs of our sponsors. We are seeking a confident leader, creative thinker, motivated problem solver, standout colleague, and life-long learner that wants to strengthen the safety and security of our country. You will join a hardworking team in an inclusive environment that cultivates intellectual curiosity, innovation and creativity.\n\nAs a Data Scientist you will...\nPrimarily design creative AI and ML algorithms as well as analytic pipelines for analyzing large-scale and complex data.\nDevelop data architectures using technologies like Hadoop, Spark, and distributed graphs to support analytic algorithms.\nBuild software applications and perform analytics on complex data.\nClearly present results to both JHU/APL and Sponsor leadership.\nPotentially travel locally to sponsor sites on an occasional basis.\nYou meet our minimum qualifications for this position if you\nPossess a B.S. in Computer Science, Information Science, Mathematics, Physics, Operations Research, or a related discipline. 1-5 years of experience.\nHave experience with statistics, machine learning algorithms, or general algorithm development.\nHave a knowledge of modern large-scale data systems and architectures.\nPossess solid software development skills.\nExhibit excellent social skills, the ability to work independently, excellent written and oral communications skills, and good organizational skills.\nAre able to obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.\nYoull go above and beyond our minimum requirements if you\nHave a M.S. or Ph.D. in the disciplines listed above, and have working knowledge of state-of-the-art large-scale data approaches and architectures. e.g. experience with quantum algorithms.\nAre experienced with software engineering processes and techniques.\nWhy Work at APL?\n\nThe Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nations most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.\n\nAt APL, we celebrate our differences and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APLs campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at www.jhuapl.edu/careers. | 3781 | 0 | 0 | 1 | 0 | 4.6 | Johns Hopkins University Applied Physics Laboratory\n | Laurel, MD | MD | 5001 to 10000 Employees | 1942 | 78 | Nonprofit Organization | Aerospace & Defense | Aerospace & Defense | $1 to $2 billion (USD) | 38 |
| 37 | Data Scientist | Data Scientist | na | $50K-$84K\n(Glassdoor est.) | 50 | 84 | 67.0 | 0 | 0 | Data Scientist – Auto Club Services Inc. – 9125 Henderson Road, Tampa, FL 33634– Full-time - Multiple Positions\n\nJob Description: The Data Scientist will produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data. Generate and test hypotheses and analyze and interpret the results of product experiments. Execute on defined data science problems. Work with Big Data coming from numerous sources. Extract, clean, transform and process very large amounts of structured and unstructured data to prepare for data science initiatives (data wrangling). Apply machine learning, time series and other data science techniques to forecast sales volumes, usage of products, and membership benefits. Build deployable machine learning models that can support solutions for cross selling, sentiment analysis, and improved customer experience. Research new machine learning solutions for complex business problems. Create data visualizations to illustrate findings in BI tools such as Tableau.\nRequirements: Bachelor's degree in Business Administration, Computer Science, Statistics, or a related field and 3 years of experience with statistical modeling tools (R) and scripting languages (Python or Scala) in the job offered or a related position. Must have 3 years of experience with SQL and using statistical techniques within Data Science including linear/logistic regression, decision trees and cluster analysis. Must also have 1 year of experience applying machine learning techniques to real-world problems with supervised and unsupervised learning algorithms. Will also accept Master’s degree in Business Administration, Computer Science, Statistics, or a related field and 2 years of experience as stated above.\n\nMust have legal authority to work in U.S. EEOE.\n\nPlease send us your resume via mail to: Teresa McBlair, Auto Club Services Inc., 9125 Henderson Road, Tampa, FL 33634. | 2361 | 1 | 0 | 1 | 1 | 3.1 | AAA The Auto Club Group\n | Tampa, FL | FL | 10000+ Employees | 1902 | 118 | Company - Private | Insurance Agencies & Brokerages | Insurance | $2 to $5 billion (USD) | 38 |
| 45 | Data Scientist | Data Scientist | na | $60K-$102K\n(Glassdoor est.) | 60 | 102 | 81.0 | 0 | 0 | Job Description\n\nRole Data Scientist\n\nKey Responsibilities Work cross functionally to define problem statements, collect data, find key insights, build analytical models and make recommendations.\n\nBuild and maintain key predictive, regression, causal, time-series, optimization & customer segmentation, capacity constraint models.\n\nLeverage tools like R, PHP, Python, Hadoop & Azure Data Bricks, ADF, ADLS, Azure Analysis Service to drive efficient analytics.\n\nCommunicate final recommendations and drive decision making.\n\nAbility to work independently or to manage a virtual team that will research innovative solutions to challenging business problems\n\nAbility to collaborate with team and drive analytic projects end to end,\n\nSuperior communication skills, both verbal and written\n\nAttention to detail and data accuracy\n\nBusiness reporting\n\nMandatory Skills · Degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research, Management Science).\n\n· Hands on experience in building machine learning models using algorithms such as K-Means, SVM, KNN, Tree-Based Methods as well as different forecasting techniques.\n\n· Industry experience in Data analytics/BI, Forecasting modeling and visualization, Optimization and statistics.\n\n· 5+ years of Scripting with one of these languages (R, PYTHON).\n\n· 5 or more years of overall IT/DBMS/Data Store experience.\n\n· Three or more years of experience in, big data, data caching, data federation and data virtualization management\n\n· Understand the internals of R and Python (Who can perform root cause analysis for the issues encountered in production)\n\n· Prior experience with cloud services or cloud data services and/or data analytics projects preferred - Platform knowledge (Azure, Windows and Linux)\n\n· Good knowledge of Cloud Architecture (Public and Private clouds) – AZURE, AWS\n\nDesired Skills · Expert in querying and analyzing big data using Hive, Python, SQL, Scope and/or C# · Experience working with unstructured big data (Hadoop and/or Cosmos)\n\n· Experts in advanced Excel functions (e.g., creating formulas, pivot tables) and PowerBI\n\n· Prior knowledge of data modelling and processing techniques for big data systems\n\n· Solid understanding of BI and data solutions, including Power-pivots, cubes, and datamarts.\n\n· Self-motivated, agile and driven to think out-of-the-box\n\n· Ability to influence diverse audiences and build strong partnerships with stakeholders\n\nTotal Experience Required 7 Years\n\nWork Location Redmond\n\nJob Function\n\nCONSULTANCY\n\nRole\n\nDeveloper\n\nJob Id\n\n161371\n\nDesired Skills\n\nAzure | Machine Learning | Python | T SQL | 2645 | 1 | 1 | 1 | 0 | 3.7 | Tata Consultancy Services (North America)\n | Redmond, WA | WA | 10000+ Employees | 1968 | 52 | Subsidiary or Business Segment | IT Services | Information Technology | $10+ billion (USD) | 38 |
| 46 | Data Scientist | Data Scientist | na | $60K-$89K\n(Glassdoor est.) | 60 | 89 | 74.5 | 0 | 0 | Role Overview:\n\nLooking for data scientists that will help us discover and leverage digital retail data to help our clients drive top line sales and add meaningful value to their businesses. Primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated into our various platforms. In addition, applying advanced machine learning techniques where appropriately to improve performance of the Decision Science solutions.\n\nKey Accountabilities:\nOwn data science projects through full cycle implementation\nPerform analysis to predict outcomes based on business questions/problems\nProcessing, cleansing, and verifying the integrity of data used for analysis including normalization, standardization, PCA, correlation, data wrangling, etc.\nSelecting features, building and optimizing classifiers using machine learning techniques\nData mining using state-of-the-art methods including but not limited to K-means, kNN, Neural Networks, Decision Trees, Random Forests, Logistic Regression, Linear/Multiple Regression, etc\nDoing ad-hoc analysis and presenting results in a clear manner\nMarket Mix Models\nQuantify what drove sales changes looking at metrics such as Average Selling Price, Out of Stock, Coupons, Discounts, Media attributed clicks, etc.\nUtilize results to help our clients make better investment choices to drive incremental sales\nIntegrate models into our internal dashboard to visualize and make output of models easily accessible\nMedia Analytics\nParticipate in media innovation groups to test and learn new ways of setting up and running media campaigns on Amazon (AMS, AAP), and other online retailers including but not limited to Instacart, Walmart, Target, Kroger, Shipt, etc.\nDevelop and test models to move from manual and rule-based campaign management to programmatic campaign management\nHypothesis Testing\nPerform hypothesis testing to better understand data sets and comparison of data sets.\nThe following tests might include but are not limited to Normality Testing, T-Test, Chi-Square Test, ANOVA, HOV, etc.\nCoach team members less experience in the field of ML\nSkills, Experience, Qualifications Required:\nWe’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field\nExperience with programmatic media, Google ads, Facebook Advertising, etc. is a plus\nExperience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc\nExperience querying databases and using statistical computer languages: R, Python, SQL, etc. Excellence in at least R or Python is highly desirable\nExperience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.\nExperience with data visualisation tools, such as D3.js, GGplot, Tableau, etc.\nExcellent written and verbal communication skills for coordinating across teams\nWhat we offer:\nOur benefits package incorporates what we’re passionate about – unlocking your future, overall well-being, and sustainability – whilst giving you control over your benefits.\nUnlimited Paid Time Off\n401K – Saving Incentive plan\nMedical and Dental Insurance plans\nFlexible Spending Accounts\nVision benefits\nGreat learning and development opportunities\nLife Assurance and Disability insurance\nOption to opt into the Ascential Shares Scheme\nAbout Flywheel\n\nFlywheel Digital is a diverse collection of practitioners who have solved the most challenging problems for numerous Fortune 500 companies on Amazon. We love rolling up our sleeves to figure out the root cause of issues and implement structural fixes to get and keep our client's business on track. Our team of business managers, search managers, analysts, and software developers work together to provide industry-leading support to the best brands on Amazon. Flywheel are headquartered in Baltimore in the United States and have recently set up a European hub in London. In 2018 Flywheel was acquired by Ascential PLC.\n\nWant more info?\n\nFind out more on what our people say:\n\nAscential YouTube Channel\n\nIf we inspire you, why not join and inspire us? | 4312 | 1 | 1 | 1 | 1 | 3.6 | WGSN\n | Baltimore, MD | MD | 1 to 50 Employees | 1998 | 22 | Company - Private | Consulting | Business Services | $50 to $100 million (USD) | 38 |